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Статті в журналах з теми "Medical details"

Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 травня 2022

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1

Kojima, Takako, and Edward Barroga. "Further Details of a New Freely Accessible Medical Writing Site." Japanese Journal of Gastroenterological Surgery 47, no. 1 (2014): 80–82. http://dx.doi.org/10.5833/jjgs.2014.sc001.

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2

Davies, T. M. "Medical details crucial for residential care." BMJ 306, no. 6885 (April 24, 1993): 1130. http://dx.doi.org/10.1136/bmj.306.6885.1130-a.

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3

McGreevy, Jolion, and Rosamond Rhodes. "Triage: Medical Details and Words Matter." American Journal of Bioethics 21, no. 11 (October 28, 2021): 64–67. http://dx.doi.org/10.1080/15265161.2021.1980145.

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4

&NA;. "FDA Details New Medical Device Innovation Initiative." Journal of Clinical Engineering 31, no. 3 (July 2006): 129–33. http://dx.doi.org/10.1097/00004669-200607000-00013.

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5

Hooper, Vallire D. "Safety: focus on the details." Journal of PeriAnesthesia Nursing 19, no. 1 (February 2004): 1–3. http://dx.doi.org/10.1016/j.jopan.2003.12.001.

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6

BARNES, S. "Preparing for surgery: Providing the details." Journal of PeriAnesthesia Nursing 16, no. 1 (February 2001): 31–32. http://dx.doi.org/10.1016/s1089-9472(01)40964-6.

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7

Tan, Yunlan, Guangyao Li, Huixian Duan, and Chao Li. "Enhancement of Medical Image Details via Wavelet Homomorphic Filtering Transform." Journal of Intelligent Systems 23, no. 1 (January 1, 2014): 83–94. http://dx.doi.org/10.1515/jisys-2013-0061.

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AbstractA new medical image enhancement algorithm based on spatial frequency domain is presented in this article. The medical image is first divided into several sub-images based on dyadic wavelet scale analysis. At each level, different directional sub-band images can reflect the different characteristics of the image. A low-frequency sub-band image maintains the original image content information, and high-frequency sub-band images represent image details such as edges and regional boundaries. The corresponding sub-band images are then enhanced by different Butterworth homomorphic filtering functions, which can attenuate the low frequencies and amplify the high frequencies. A linear adjustment is carried out on the low frequency of the highest level. Then, the wavelet reconstruction course is used to obtain the final enhanced image. Experiments on magnetic resonance images of temporomandibular joint soft tissues have shown that the proposed method can effectively eliminate the non-uniform luminance distribution of medical images. Its performance is much better than traditional Butterworth homomorphic filtering algorithm whether in subjective vision quality or objective evaluations such as detailed information entropy and average gradient.

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8

Nagaraju, G., P. Pardhasaradhi, and V. S. Ghali. "A New Watermarking Scheme for Medical Images with Patient’s Details." International Journal of Engineering & Technology 7, no. 3.31 (August 24, 2018): 25. http://dx.doi.org/10.14419/ijet.v7i3.31.18194.

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A brain tumor is a mass of cells in your brain that are not normal.Some brain tumors contain cancer and others don't: Brain tumor include both, benign and malignant forms. Benign brain tumors don't have cancer cells. Malignant brain tumors have cancer cells. Differentiating malignant and benign cases is a hard task even for experienced specialists. This work presents how to extract the characteristics and features of tumor image by general segmentation methods for malignant risk computation and presents the use of digital watermarking for applications of automated tumor image analysis. Here personal information such as name, age, gender, location, ADHAAR number, contact number etc., and tumor information such as tumor types, area of the tumor, severity, and any other useful information are embedded to the tumor image. Encrypting that image with well-known encryption algorithms is also possible to avoid unnecessary nuisance from information hackers.

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9

Chiroiu, Veturia, Ligia Munteanu, Rodica Ioan, Ciprian Dragne, Cristian Rugină, and Luciana Majercsik. "Using the Sonification for Hardly Detectable Details in Medical Images." International Journal of Scientific and Research Publications (IJSRP) 9, no. 7 (July 12, 2019): p9146. http://dx.doi.org/10.29322/ijsrp.9.07.2019.p9146.

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10

Wang, Lifang, Chaoyu Shi, Suzhen Lin, Pinle Qin, and Yanli Wang. "Convolutional Sparse Representation and Local Density Peak Clustering for Medical Image Fusion." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 07 (October 22, 2019): 2057003. http://dx.doi.org/10.1142/s0218001420570037.

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Aiming at the problem of insufficient detail retention in multimodal medical image fusion (MMIF) based on sparse representation (SR), an MMIF method based on density peak clustering and convolution sparse representation (CSR-DPC) is proposed. First, the base layer is obtained based on the registered input image by the averaging filter, and the original image minus the base layer to obtain the detail layer. Second, for retaining the details of the fused image, the detail layer image is fused by CSR to obtain the fused detail layer image, then the base layer image is segmented into several image blocks, and the blocks are clustered by using DPC to obtain some clusters, and each class cluster is trained to obtain a sub-dictionary, and all the sub-dictionaries are fused to obtain an adaptive dictionary. The sparse coefficient is fused through the learned adaptive dictionary, and the fused base layer image is obtained through reconstruction. Finally, fusing the detail layer and the base layer and reconstructing them forms the ultimate fused image. Experiments show that compared to the state-of-the-art two multi-scale transformation methods and five SR methods, the proposed method(CSR-DPC) outperforms the other methods in terms of the image details, the visual quality and the objective evaluation index, which can be helpful for clinical diagnosis and adjuvant treatment.

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11

Mandell, L. A., P. B. Iannini, and G. S. Tillotson. "Respiratory Fluoroquinolones: Differences in the Details." Clinical Infectious Diseases 38, no. 9 (May 1, 2004): 1331–32. http://dx.doi.org/10.1086/383153.

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12

Breedlove, Byron, and Reginald Tucker. "Revealing Details in Light and Shadows." Emerging Infectious Diseases 24, no. 5 (May 2018): 957–58. http://dx.doi.org/10.3201/eid2405.ac2405.

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13

Zhang, Guo, Jinzhao Lin, Enling Cao, Yu Pang, and Weiwei Sun. "A Medical Endoscope Image Enhancement Method Based on Improved Weighted Guided Filtering." Mathematics 10, no. 9 (April 23, 2022): 1423. http://dx.doi.org/10.3390/math10091423.

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In clinical surgery, the quality of endoscopic images is degraded by noise. Blood, illumination changes, specular reflection, smoke, and other factors contribute to noise, which reduces the quality of an image in an occluded area, affects doctors’ judgment, prolongs the operation duration, and increases the operation risk. In this study, we proposed an improved weighted guided filtering algorithm to enhance endoscopic image tissue. An unsharp mask algorithm and an improved weighted guided filter were used to enhance vessel details and contours in endoscopic images. The scheme of the entire endoscopic image processing, which included detail enhancement, contrast enhancement, brightness enhancement, and highlight area removal, is presented. Compared with other algorithms, the proposed algorithm maintained edges and reduced halos efficiently, and its effectiveness was demonstrated using experiments. The peak signal-to-noise ratio and structural similarity of endoscopic images obtained using the proposed algorithm were the highest. The foreground–background detail variance–background variance improved. The proposed algorithm had a strong ability to suppress noise and could maintain the structure of original endoscopic images, which improved the details of tissue blood vessels. The findings of this study can provide guidelines for developing endoscopy devices.

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14

Tuffs, A. "Obituary of past president of German Medical Association omits details of Nazi past, medical historians say." BMJ 341, aug16 1 (August 16, 2010): c4468. http://dx.doi.org/10.1136/bmj.c4468.

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15

Rosales, Mª José, Teresa Arnedo, and Carmen Mascaró. "Ultrastructural Details of Cryptosporidium parvum Development in Calf Intestine." Memórias do Instituto Oswaldo Cruz 93, no. 6 (November 1998): 847–50. http://dx.doi.org/10.1590/s0074-02761998000600027.

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16

Scherer, David G. "Pediatric Participation in Medical Decision Making: The Devil Is in the Details." American Journal of Bioethics 18, no. 3 (February 21, 2018): 16–18. http://dx.doi.org/10.1080/15265161.2017.1418924.

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17

Doddaiah, Sunilkumar, Deepa Bhat, Basavanagowdappa Hathur, M. N. Suma, Manjunath G. V., and Prashant Vishwanath. "Assessment and accreditation of a medical college by national assessment and accreditation council: an overview." International Journal of Advances in Medicine 7, no. 2 (January 23, 2020): 354. http://dx.doi.org/10.18203/2349-3933.ijam20200093.

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Accreditation affirms provision of quality education, thus determines its graduate attributes. WFME, WHO and various bodies have been striving to ensure credibility of educational institutions through accreditation. NAAC is an Indian accrediting body providing framework for quality assurance to higher education institutions. Being an autonomous body under UGC, it sets a standard of excellence to which they are bound to adhere. This article provides details regarding an insight into NAAC, its vision, objectives, core values and the process of accreditation. The details regarding various criteria, components, allotment of weightage to each of them are detailed in the manuscript. The requirements and needs towards preparedness for this accreditation process are simplified to make the readers to understand easily thus providing a bird’s eye view of entire process.

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18

Jie, Xiong, and Zhang Yan Qin. "Digital Medical Image Enhanced by Stationary Wavelet Transform." Applied Mechanics and Materials 239-240 (December 2012): 1219–24. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1219.

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Abstract: When a digital medical image is enhanced by Histogram Equalization, Homomorphic Filtering or multi-scales Retinex, the useful details of the image can not be strengthened. According to the imaging principle and medical requirement, a new method is proposed. The image is decomposed into illumination and reflection by wavelet illumination-reflection model. The details of the reflection are strengthened by soft-threshold method. The dynamic range of the illumination is reduced by Gaussian filtering in order to enhance the image. Experiments and analysis show that the method is obviously better than these algorithms.

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19

Underwood, David G. "Impact of AIDS/HIV on Medical Directors." Journal of Insurance Medicine 49, no. 1 (January 1, 2021): 32–36. http://dx.doi.org/10.17849/insm-49-1-32-36.1.

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20

Allen, Timothy Craig. "The Devil's in the Biorepository Details." Archives of Pathology & Laboratory Medicine 138, no. 4 (October 7, 2013): 452. http://dx.doi.org/10.5858/arpa.2013-0459-ed.

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21

Madamanchi, Nageswara R., and Marschall S. Runge. "NADPH oxidases and atherosclerosis: unraveling the details." American Journal of Physiology-Heart and Circulatory Physiology 298, no. 1 (January 2010): H1—H2. http://dx.doi.org/10.1152/ajpheart.01020.2009.

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22

Raj, Adarsh. "Neonatal Screening Application." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (February 28, 2022): 89–99. http://dx.doi.org/10.22214/ijraset.2022.39619.

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Abstract: Neonatal screening is a set of medical diagnostics that are performed on infants. Our project deals with the problem of a centralized management system for hospitals making it easier for doctors as well as patients to view reports and compare current reports with the previous reports. Our app would also help in reducing errors that are generally caused when this process of comparing and contrasting the report is done manually by doctors. The main objective of this project is to develop a Client Server based environment, for transferring the medical report details from the bio medical lab. Also to improve data analysis technique, using previous data comparison methods. This system works on accurate recording of all user report transactions lead to better data management and increases in various comparisons. This project consists of two types of interactions like admin and patient. Admin will be providing with a well secured login and patient details will be registered using admin. A user name and password will be provided to the user. The initially process is to enter the medical test requirement of the patient. The details contain prescribed doctor details, patient details and lab test details. Each disease will contain different CTA (Complete test analysis) for their test result. For example a general blood sugar test contains HBL cholesterol, LDL cholesterol, Glucose level and etc. These all said to be CTA test. Once patient has been register successfully their blood will be collected and a temporary reference number will be provided. This temporary number is for admin and employee reference. Once their blood test has been done, the test result will be uploaded by the admin by selected the corresponding user name. The uploading details will be stored in a centralized server for data utility purpose. Patient can login with their user and password. Through selecting the date, the patient can view their current test result from their home itself. A test history option will be provided to the patient. So that patient can compare their test with their previous test results. This option makes the patient to manage and know about their health condition and their treatment. An interactive grid and chart will be generated for furnishing the result to the patient. Admin can maintain their patient detail, patient count, test results and etc. This makes more comfortable communication between admin and patients. Also entire treatment record will be computerized for future references.

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23

Anjana, Ranjit Mohan, Rajendra Pradeepa, Mohan Deepa, Manjula Datta, Vasudevan Sudha, Ranjit Unnikrishnan, Lalith M. Nath, et al. "The Indian Council of Medical Research—India Diabetes (ICMR-INDIAB) Study: Methodological Details." Journal of Diabetes Science and Technology 5, no. 4 (July 2011): 906–14. http://dx.doi.org/10.1177/193229681100500413.

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24

Dhawan, Sumeet R., and Naveen Sankhyan. "Additional Details for Improved Reporting of Tuberculous Meningitis Studies." Clinical Infectious Diseases 64, no. 12 (April 5, 2017): 1804–5. http://dx.doi.org/10.1093/cid/cix309.

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25

Master, Stephen R. "Getting the Details Right: Gene Signatures for Cancer Therapy." Clinical Chemistry 56, no. 9 (September 1, 2010): 1378–80. http://dx.doi.org/10.1373/clinchem.2010.147686.

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26

Tan, Ling, and Xin Yu. "Medical Image Fusion Based on Fast Finite Shearlet Transform and Sparse Representation." Computational and Mathematical Methods in Medicine 2019 (March 3, 2019): 1–14. http://dx.doi.org/10.1155/2019/3503267.

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Анотація:

Clinical diagnosis has high requirements for the visual effect of medical images. To obtain rich detail features and clear edges for fusion medical images, an image fusion algorithm FFST-SR-PCNN based on fast finite shearlet transform (FFST) and sparse representation is proposed, aiming at the problem of poor clarity of edge details that is conducive to maintaining the details of source image in current algorithms. Firstly, the source image is decomposed into low-frequency coefficients and high-frequency coefficients by FFST. Secondly, the K-SVD method is used to train the low-frequency coefficients to obtain the overcomplete dictionary D, and then the OMP algorithm sparsely encodes the low-frequency coefficients to complete the fusion of the low-frequency coefficients. Then, a high-frequency coefficient is applied to excite a pulse-coupled neural network, and the fusion coefficient of the high-frequency coefficient is selected according to the number of ignitions. Finally, the fused low-frequency coefficient and high-frequency coefficient are reconstructed into the fused medical image by FFST inverse transform. The experimental results show that the image fusion result of the proposed algorithm is about 35% higher than the comparison algorithms for the edge information transfer factor QAB/F index and has achieved good results in both subjective visual effects and objective evaluation indicators.

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27

Xiao, Kai, Jianli Li, Shuangjiu Xiao, Haibing Guan, Fang Fang, and Aboul Ella Hassanien. "Fuzzy Clustering with Multi-Resolution Bilateral Filtering for Medical Image Segmentation." International Journal of Fuzzy System Applications 3, no. 4 (October 2013): 47–59. http://dx.doi.org/10.4018/ijfsa.2013100104.

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Although fuzzy c-means (FCM) algorithm and some of its variants have been extensively widely used in unsupervised medical image segmentation applications in recent years, they more or less suffer from either noise sensitivity or loss of details, which always is a key point to medical image processing. This paper presents a novel FCM variation method that is suitable for medical image segmentation. The proposed method, typically by incorporating multi-resolution bilateral filter which is combined with wavelet thresholding, provides the following advantages: (1) it is less sensitive to both high- and low-frequency noise and removes spurious blobs and noisy spots, (2) it yields more homogeneous clustering regions, and (3) it preserves detail, thus significantly improving clustering performance. By the use of synthetic and multiple-feature magnetic resonance (MR) image data, the experimental results and quantitative analyses suggest that, compared to other fuzzy clustering algorithms, the proposed method further enhances the robustness to noisy images and capacity of detail preservation.

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28

Aijing, Luo, and Yin Jin. "Research on an Improved Medical Image Enhancement Algorithm Based on P-M Model." Open Biomedical Engineering Journal 9, no. 1 (August 31, 2015): 209–13. http://dx.doi.org/10.2174/1874120701509010209.

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Image enhancement can improve the detail of the image to achieve the purpose of the identification of the image. At present, the image enhancement is widely used in medical images, which can help doctor’s diagnosis. IEABPM (Image Enhancement Algorithm Based on P-M Model) is one of the most common image enhancement algorithms. However, it may cause the loss of the texture details and other features. To solve the problems, this paper proposes an IIEABPM (Improved Image Enhancement Algorithm Based on P-M Model). The simulation demonstrates that IIEABPM can effectively solve the problems of IEABPM, and improve image clarity, image contrast, and image brightness.

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29

Díaz-Zagal, S., C. Gutiérrez-Estrada, E. Rendón-Lara, I. Abundez-Barrera, and J. H. Pacheco-Sánchez. "Pneumatic Artificial Mini-Muscles Conception: Medical Robotics Applications." Applied Mechanics and Materials 15 (August 2009): 49–54. http://dx.doi.org/10.4028/www.scientific.net/amm.15.49.

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Actually, the pneumatic artificial muscles of McKibben type [1] show a great functional similarity with the skeletal muscle. A detailed analysis of the system has been performed to better characterize this similarity with the analogous dynamic behavior of the organic system. Such analysis has shown that the McKibben-type artificial muscle can be adapted to the Hill fundamental model [2]. Research regarding pneumatic artificial muscle with application to robotics has recently focused on mini-actuators for miniaturized robotics systems. This is specially true in the area of medical robotics, but an extension of miniactuator technology to other applications may be feasible, such as the development of artificial fine-motion limbs (hands and/or fingers). The present work details the artificial muscle miniaturization process developed in the LESIA laboratory, their behavior, their position and force control characteristics, as well as the possible applications of this technology to medical robotics.

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30

Stevens, Richard M., and Eoghan Casey. "Extracting Windows command line details from physical memory." Digital Investigation 7 (August 2010): S57—S63. http://dx.doi.org/10.1016/j.diin.2010.05.008.

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31

McLaren, Jami. "Medical Device Sterilization Modality Selection Decision Process." Biomedical Instrumentation & Technology 54, s1 (June 1, 2020): 6–14. http://dx.doi.org/10.2345/0899-8205-54.s3.6.

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Abstract Selection of an appropriate sterilization modality requires an understanding of certain key aspects of the product under consideration. Primary aspects to be considered include understanding of the product's intended use and details of the product design. This article reviews these primary considerations for sterilization modality selection and demonstrates the sterilization modality selection process through several example case studies.

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32

Herman, Amir, Netta Notzer, Zipi Libman, Rony Braunstein, and David M. Steinberg. "Statistical education for medical students—Concepts are what remain when the details are forgotten." Statistics in Medicine 26, no. 23 (2007): 4344–51. http://dx.doi.org/10.1002/sim.2906.

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33

Herman, Amir, Netta Notzer, Zipi Libman, Rony Braunstein, and David M. Steinberg. "Statistical education for medical students—concepts are what remain when the details are forgotten." Statistics in Medicine 27, no. 12 (2008): 2268–69. http://dx.doi.org/10.1002/sim.3248.

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34

Bae, Jang Won, Kyohong Shin, Hyun-Rok Lee, Hyun Jin Lee, Taesik Lee, Chu Hyun Kim, Won-Chul Cha, Gi Woon Kim, and Il-Chul Moon. "Evaluation of Disaster Response System Using Agent-Based Model With Geospatial and Medical Details." IEEE Transactions on Systems, Man, and Cybernetics: Systems 48, no. 9 (September 2018): 1454–69. http://dx.doi.org/10.1109/tsmc.2017.2671340.

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35

Hristoskova, Anna, Dieter Moeyersoon, Sofie Van Hoecke, Stijn Verstichel, Johan Decruyenaere, and Filip De Turck. "Dynamic composition of medical support services in the ICU: Platform and algorithm design details." Computer Methods and Programs in Biomedicine 100, no. 3 (December 2010): 248–64. http://dx.doi.org/10.1016/j.cmpb.2010.03.019.

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36

Hu, Qian, Ning Liu, Jing Wang, Zhichao Wu, Xuan Zhang, Qiang Liu, Yixin Zhao, and Feng Xu. "An overlapping sequence tagging mechanism for symptoms and details extraction on Chinese medical records." Computers & Electrical Engineering 91 (May 2021): 107019. http://dx.doi.org/10.1016/j.compeleceng.2021.107019.

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37

Park, Hyeryun, Kyungmo Kim, Seongkeun Park, and Jinwook Choi. "Medical Image Captioning Model to Convey More Details: Methodological Comparison of Feature Difference Generation." IEEE Access 9 (2021): 150560–68. http://dx.doi.org/10.1109/access.2021.3124564.

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38

Petrone, Andrew B., April DuCott, Joshua J. Gagne, Sengwee Toh, and Judith C. Maro. "The Devil's in the details: Reports on reproducibility in pharmacoepidemiologic studies." Pharmacoepidemiology and Drug Safety 28, no. 5 (March 6, 2019): 671–79. http://dx.doi.org/10.1002/pds.4730.

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39

A, Karambhe, Dhandge G, Mahakal N, Jadhav S, and Hadole S. "Sacrament of Medical Importance: A Detailed Review." International journal of Indian medicine 03, no. 02 (2022): 21–27. http://dx.doi.org/10.55552/ijim.2022.2303.

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Анотація:

Early age of a human being especially infancy and childhood are the periods when there occurs the rapid physical growth, cognitive and emotional development. Therefore, this period is a very crucial period of a human life. There are some ways by using which all these developments can be enhanced up to certain levels. Samskars are thought to improve the healthy progeny's intellect, to achieve optimum mental, physical, social and spiritual growth and development, minimize the Garbhopghatakar bhav (teratological disorders) etc. Therefore, it is very important to study the Samskars in detail. For this study, all the available information regarding Shodash Samskars has been searched from classical texts, syllabus books, online journals, authorized websites etc. The information collected was thoroughly reviewed, discussed and conclusions were drawn. This study was conducted to revalidate the importance of Samskars in human life especially the infancy. In all the classical texts the no. of Samskars found were almost same i.e. 16, though name of some Samskars were found different. Out of 16, sacraments of medical importance were mainly found to be 7. Their names and medical importance are discussed in the above study in details.

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40

Rankin, Andrew. "Medical or cosmetic? The challenges of differentiating between the two." Journal of Aesthetic Nursing 10, no. 5 (June 2, 2021): 220–21. http://dx.doi.org/10.12968/joan.2021.10.5.220.

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41

"Details of Laboratory Work for Medical Students." Biomedical and Medical Science, December 18, 2020, 43–52. http://dx.doi.org/10.51231/2667-9507-2021-001-01-43-52.

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DOI 10.51231/2667-9507-2021-001-01-43-52 In the modern world of pandemics, a special place is occupied by the problems of education in the field of medicine. In developed countries, medical education remains combined. Practical training of students in the laboratories of the university is very important. The article describes a biochemistry laboratory class protocol. This protocol is described in order to create an opportunity for students to apply by doing the theoretical concepts underlying biomolecules and vesicles properties, together with the principles of centrifugation and colorimetric methodologies. The aims, objectives, methodology of teaching/learning, and assessment for this laboratory class are indicated. The proposed protocol for a laboratory class described us creates the opportunity for undergraduate students to perform experiments, to reason, and to discuss some related biochemical concepts, namely protein characterization and properties of specific staining reactions; enzyme quantification by enzymatic reaction; composition and biochemical properties of exovesicles; amphiphilic biomolecules properties; and principles and applications of centrifugation methods. This work was supported by Portuguese Ministry of Science and Higher Education (MCES).

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"Poster Details." Drug Metabolism and Pharmacokinetics 35, no. 1 (2020): S100—S113. http://dx.doi.org/10.1016/s1347-4367(20)30393-1.

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Editorial, CUAJ. "COSMiC details." Canadian Urological Association Journal 9, no. 1-2 (February 5, 2015). http://dx.doi.org/10.5489/cuaj.2788.

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A Canadian Observational Study in Metastatic Cancer of the Prostate: A Study of ZYTIGA Use in the Community Urology Setting. The COSMiC Prospective Prostate Cancer Registry.The purpose of this non-interventional, prospective, observational study is to temporally evaluate the impact of abiraterone acetate (ZYTIGA) therapy on Patient Reported Outcomes (PROs) and on clinical outcomes in the chemotherapy-naive metastatic castrate-resistant prostate cancer (mCRPC) population.Study participants must have a confirmed diagnosis of mCRPC according to medical history and have rising PSA levels or radiographic progression (documented by previous positive bone scan or metastatic lesions identified on CT or MRI) despite ongoing conventional ADT.Study participants will complete Quality of Life and Patient Satisfaction questionnaires longitudinally at defined time points. Safety and efficacy data, as well as levels of health care resource utilization associated with ZYTIGA therapy, will also be prospectively collected and analyzed.Once enrolled, study participants will be followed for a maximum of 72 weeks from the time of initiation of ZYTIGA treatment, or up to the time of early study withdrawal/termination.For additional information please contact Richard K. Plante at rplante@its.jnj.com

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"Contact Details." Cardiovascular Research 87, Supplement 1 (June 17, 2010): S3. http://dx.doi.org/10.1093/cvr/cvq170.

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"Session details: Medical image modeling tools and applications." Communications of the ACM 48, no. 2 (February 2005). http://dx.doi.org/10.1145/3263842.

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Adams, Emily M., and Caroline Erolin. "The devil is in the details: developing a modern methodology for detailed medical illustrations." Journal of Visual Communication in Medicine, May 14, 2021, 1–20. http://dx.doi.org/10.1080/17453054.2021.1921566.

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"IOP-details." International Journal of Psychophysiology 89, no. 2 (August 2013): ii. http://dx.doi.org/10.1016/s0167-8760(13)00232-8.

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"IOP-details." International Journal of Psychophysiology 90, no. 1 (October 2013): ii. http://dx.doi.org/10.1016/s0167-8760(13)00270-5.

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"IOP-details." International Journal of Psychophysiology 90, no. 2 (November 2013): ii. http://dx.doi.org/10.1016/s0167-8760(13)00293-6.

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"IOP-details." International Journal of Psychophysiology 91, no. 1 (January 2014): ii. http://dx.doi.org/10.1016/s0167-8760(14)00014-2.

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