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Journal articles on the topic 'Diagnosis'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 November 2024

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1

Bergan, John R. "Diagnosis of diagnosis diagnosed." Professional School Psychology 3, no. 2 (1988): 135–40. http://dx.doi.org/10.1037/h0090555.

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2

Alessi, Galen. "Diagnosis diagnosed: A systemic reaction." Professional School Psychology 3, no. 2 (1988): 145–51. http://dx.doi.org/10.1037/h0090554.

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3

Meyers, Joel. "Diagnosis diagnosed: Twenty years after." Professional School Psychology 3, no. 2 (1988): 123–34. http://dx.doi.org/10.1037/h0090556.

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4

Mashkov, V., and O. Mashkov. "Interpretation of diagnosis problem of system level self-diagnosis." Mathematical Modeling and Computing 2, no. 1 (July 1, 2015): 71–76. http://dx.doi.org/10.23939/mmc2015.01.071.

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5

Rele, Mayur, and Dipti Patil. "Revolutionizing Liver Disease Diagnosis: AI-Powered Detection and Diagnosis." International Journal of Science and Research (IJSR) 12, no. 11 (November 5, 2023): 401–7. http://dx.doi.org/10.21275/sr231105021910.

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6

Wykes, Til, and Felicity Callard. "Diagnosis, diagnosis, diagnosis: towards DSM-5." Journal of Mental Health 19, no. 4 (July 16, 2010): 301–4. http://dx.doi.org/10.3109/09638237.2010.494189.

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7

Wong, Bernice Y. ""Diagnosis diagnosed: Twenty years after": Comment." Professional School Psychology 3, no. 2 (1988): 141–43. http://dx.doi.org/10.1037/h0090558.

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8

Makras, Polyzois, Georgios Toloumis, Dimitrios Papadogias, Gregory Kaltsas, and Michael Besser. "The diagnosis and differential diagnosis of endogenous Cushing?s syndrome." HORMONES 5, no. 4 (October 15, 2006): 231–50. http://dx.doi.org/10.14310/horm.2002.11189.

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9

Brems, Christiane, Mark E. Johnson, Randall Burns, and Nicholas Kletti. "Dual Diagnosis: Variations Across Differing Comorbid Diagnoses." Journal of Dual Diagnosis 2, no. 3 (July 24, 2006): 109–29. http://dx.doi.org/10.1300/j374v02n03_10.

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10

Agarwal, Saumya, and Mamta Gupta. "Diagnostic Accuracy of Cytological Sampling Techniques by Bronchoscopy in the Diagnosis of Lung Cancer." Annals of Pathology and Laboratory Medicine 5, no. 5 (May 29, 2018): A354–361. http://dx.doi.org/10.21276/apalm.1720.

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11

Lembcke, Bernhard. "Diagnosis, Differential Diagnoses, and Classification of Diverticular Disease." Visceral Medicine 31, no. 2 (2015): 95–102. http://dx.doi.org/10.1159/000380833.

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12

Basha, James, Jenna M. Iwasenko, and William Rawlinson. "Diagnosis of herpesviruses and approaches to difficult diagnoses." Microbiology Australia 31, no. 3 (2010): 115. http://dx.doi.org/10.1071/ma10115.

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Herpesviruses are a ubiquitous family of DNA viruses, with 40?60% of the adult population seropositive for cytomegalovirus (CMV), and more than 90% for Epstein-Barr virus (EBV) and varicella zoster virus (VZV). Following primary infection, herpesviruses become latent in the host and may reactivate during periods of immunosuppression, such as in transplant recipients, HIV-positive patients and pregnant women. The clinical course following reactivation presents a screening and diagnostic challenge, particularly as reactivation in immunosuppressed patients may have a clinical presentation consistent with many different infections. For example, CMV pneumonitis produces disease clinically consistent with other viral pneumonias such as influenza infection. It is, therefore, imperative to obtain as relevant and accurate diagnostic information to correctly diagnose herpesvirus infections.
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13

Welton, John M., and Edward J. Halloran. "Nursing Diagnoses, Diagnosis-Related Group, and Hospital Outcomes." JONA: The Journal of Nursing Administration 35, no. 12 (December 2005): 541–49. http://dx.doi.org/10.1097/00005110-200512000-00008.

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14

Abu-Jeyyab, Mohammad. "Incidental Intra Laparoscopic Cholecystectomy Diagnosis of a Gallbladder Agenesis, A Rare Diagnosis." Gastroenterology & Hepatology International Journal 7, no. 2 (August 30, 2022): 1–4. http://dx.doi.org/10.23880/ghij-16000200.

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Gallbladder agenesis is quite a rare anomaly; it’s probably due to an embryologic mishap within the development of the hepatobiliary bud and is predominately associated with other congenital abnormalities. Most patients will stay asymptomatic; however, some will develop symptoms that mimic those of biliary, urinary, or gastrointestinal disorders. Symptoms typically appear within the fourth or fifth decade of patient life. For these reasons, gallbladder agenesis might be misdiagnosed. Leading to unnecessary surgery. This paper reports a case of gallbladder agenesis of a 41-year-old male. Presented with history of right upper quadrant abdominal pain associated with nausea and vomiting. Based on the clinical presentation and ultrasonography findings, symptomatic cholelithiasis was misdiagnosed. He was then seen by the surgical team as a case of acute cholecystitis. Imaging modalities commonly used in investigation of biliary disease symptoms where employed. Ultrasound and MRCP were done. However, findings have led to the diagnosis of acute cholecystitis and eventually to a laparoscopic cholecystectomy. This case has also shown that gallbladder agenesis can still be misdiagnosed, leading to the detection of gallbladder agenesis in the operating room
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15

Büyükbayrak, Fuat. "An evaluation of diagnostic sensitivity of transthoracic echocardiography in diagnosis of post-cardiac surgery tamponade." Turkish Journal of Thoracic and Cardiovascular Surgery 22, no. 1 (January 21, 2014): 35–42. http://dx.doi.org/10.5606/tgkdc.dergisi.2014.9014.

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16

Dr. Nupur Sah, Dr Nupur Sah, Dr Hemant Bhutani, and Dr Priyadarshini Shetty. "Halitosis – Etiology and Diagnosis." Indian Journal of Applied Research 3, no. 11 (October 1, 2011): 352–54. http://dx.doi.org/10.15373/2249555x/nov2013/109.

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17

Hron, J. "Diagnosis of business health." Agricultural Economics (Zemědělská ekonomika) 50, No. 12 (February 24, 2012): 535–42. http://dx.doi.org/10.17221/5245-agricecon.

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Every business grows, develops and dies within its life-cycle, dependent on its relations with the external and internal environment. Its “flexibility” and ability to “influence” both the internal and external environment are indications of its “health”. A healthy business is characterized by those parameters of its structure and behaviour that encourage its further development in any given environment. The “health” of the business is determined by the level of its homeostasis with the internal and external environment. This kind of health may reach various levels. It is therefore necessary to diagnose it, and to suggest changes in its business strategy and individual parameters. The health of a business should therefore represent a prerequisite of effective behaviour.
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18

Gulhane, Dr Sushma R., Dr Madhuri S. Kate, and Dr Smita Sonawane. "Cytological Diagnosis of Rhinoscleroma." International Journal of Scientific Research 3, no. 7 (June 1, 2012): 329–31. http://dx.doi.org/10.15373/22778179/july2014/97.

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19

Shimoda, Tetsuya, and Tetsushi Yamagami. "What is your Diagnosis?" Journal of Japan Veterinary Cancer Society 3, no. 2 (2012): GIJU7—GIJU10. http://dx.doi.org/10.12951/jvcs.2012-993.

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20

Irie, Mituhiro, and Tetsushi Yamagami. "What is your Diagnosis ?" Journal of Japan Veterinary Cancer Society 3, no. 1 (2012): GIJU1—GIJU6. http://dx.doi.org/10.12951/jvcs.2012-999.

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21

Takahashi, Masashi. "What is your Diagnosis?" Journal of Japan Veterinary Cancer Society 4, no. 2 (2013): GIJU5—GIJU8. http://dx.doi.org/10.12951/jvcs.2013-994.

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22

Matsuyama, Fumiko. "What is your Diagnosis?" Journal of Japan Veterinary Cancer Society 4, no. 1 (2013): GIJU1—GIJU4. http://dx.doi.org/10.12951/jvcs.2013-999.

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23

Ito, Tetsuro. "What is your Diagnosis?" Journal of Japan Veterinary Cancer Society 5, no. 1 (2014): GIJU1—GIJU6. http://dx.doi.org/10.12951/jvcs.2014-999.

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24

Das, Subhashis. "Artificial Intelligence in Diagnosis." JOURNAL OF CLINICAL AND BIOMEDICAL SCIENCES 13, no. 4 (December 28, 2023): 100–101. http://dx.doi.org/10.58739/jcbs/v13i4.editorial.

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25

Fellowes, Sam. "Self-Diagnosis in Psychiatry and the Distribution of Social Resources." Royal Institute of Philosophy Supplement 94 (September 28, 2023): 55–76. http://dx.doi.org/10.1017/s1358246123000218.

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AbstractI suggest that the diagnosis that an individual self-diagnoses with can be influenced by levels of public awareness. Accurate diagnosis requires consideration of multiple diagnoses. Sometimes, different diagnoses can overlap with one another and can only be differentiated in subtle and nuanced ways, but particular diagnoses vary considerably in levels of public awareness. As such, an individual may meet the diagnostic criteria for one diagnosis but self-diagnoses with a different diagnosis because it is better known. I then outline a potential negative consequence of this. Psychiatric diagnoses can grant access to what I call social resources, namely, political advocacy, campaigning for support, participating in scientific research, building diagnostic cultures, and opportunity for social interactions with people who have the same diagnosis. The strength of the social resources for a particular diagnosis can be made stronger when more people have that diagnosis. As such, inaccurate self-diagnosis can result in the social resources for one diagnosis being strengthened whilst not being strengthened in relation to another diagnosis in comparison to accurate diagnosis. This shows how inaccurate self-diagnosis can alter the distribution of social resources. We need to consider whether this is unfair to people who are diagnosed with less well-known conditions.
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26

Kurniawan, Liong Boy, and Mansyur Arif. "DIAGNOSIS TIROID (Diagnosis of Thyroid)." INDONESIAN JOURNAL OF CLINICAL PATHOLOGY AND MEDICAL LABORATORY 21, no. 3 (April 18, 2018): 304. http://dx.doi.org/10.24293/ijcpml.v21i3.1285.

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Thyroid disease often causes unspecific or mild symptoms, so laboratory tests are needed to confirm the functional diagnosis of thethyroid disorder. The laboratory tests which are important to establish the diagnosis of thyroid disorder include: total and free thyroidhormones, its related (thyroid) hormone binding proteins and auto antibodies. The thyroid hormone tests are mostly measured withcompetitive or sandwich immunoassays and each method can be interfered by several factors. Some drugs may increase or decrease thethyroid functional tests and several factors such as: underlying diseases, age, pregnancy, occurrence of heterophil antibody and autoantibodies may also interfere the thyroid tests results. The interpretation of an unusual combination from thyroid stimulating hormonesuch as free thyroxin and tri-iodothyronine results needs confirmation of underlying condition for establishing the right diagnosis. Thisreview is aimed to evaluate several factors which may influence the thyroid tests and interpretation.
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27

Brown, James H., Allen Berkal, Samia Barakat, and Robert Mcilwraith. "Personality Diagnosis and Illness Diagnosis." Canadian Journal of Psychiatry 30, no. 6 (October 1985): 428–33. http://dx.doi.org/10.1177/070674378503000611.

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28

Brown, Phil, Mercedes Lyson, and Tania Jenkins. "From diagnosis to social diagnosis." Social Science & Medicine 73, no. 6 (September 2011): 939–43. http://dx.doi.org/10.1016/j.socscimed.2011.05.031.

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29

Zhang, Pengfei. "The Structure and Organizations of ICHD-3 Differential Diagnoses through DiffNet: A Pilot Study." Diagnostics 12, no. 11 (October 25, 2022): 2589. http://dx.doi.org/10.3390/diagnostics12112589.

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Differential diagnosis is fundamental to medicine. Using DiffNet, a differential diagnosis generator, as a model, we studied the structure and organization of how collections of diagnoses (i.e., sets of diagnoses) are related in the ICHD3. Furthermore, we explored the clinical and theoretical implication of these answers. Methods: DiffNet is a freely distributed differential diagnosis generator for headaches using graph theoretical properties of ICHD3: (1) DiffNet considers each ICHD3 diagnosis as a node. (2) An edge exists between two ICHD3 diagnoses if they are connected by either classification hierarchy or are cross-referenced in ICHD3 comment section. In the current project, we generated a set of differential diagnoses using DiffNet for each ICHD3 diagnosis. We then determined algorithmically the set/subset relationship between these sets. We also determined the smallest list of ICHD3 diagnosis whose differential diagnoses would encompass the totality of ICHD3 diagnoses. Results: All ICHD3 diagnoses can be represented by a minimum of 92 differential diagnosis sets. Differential diagnosis sets for 10 of the 14 first digit subcategories of ICHD3 are represented by more than one differential diagnosis sets. Fifty-one of the 93 differential diagnosis sets contain multiple subset relationships; the remaining 42 do not enter into any set/subset relationship with other differential diagnosis sets. Finally, we included a hierarchical presentation of differential diagnosis sets in ICHD3 according to DiffNet. Conclusion: We propose a way of interpreting headache differential diagnoses as partial ordered sets (i.e., poset). For clinicians, fluency in the 93 diagnoses and their differential, as put forth here, implies a complete description of ICHD3. On a theoretical level, interpreting ICHD3 differential diagnosis as poset allows for researchers to translate differential diagnoses sets topologically, algebraically, and categorically.
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30

Elmishali, Amir, Roni Stern, and Meir Kalech. "Data-Augmented Software Diagnosis." Proceedings of the AAAI Conference on Artificial Intelligence 30, no. 2 (February 18, 2016): 4003–9. http://dx.doi.org/10.1609/aaai.v30i2.19076.

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Software fault prediction algorithms predict which software components is likely to contain faults using machine learning techniques. Software diagnosis algorithm identify the faulty software components that caused a failure using model-based or spectrum based approaches. We show how software fault prediction algorithms can be used to improve software diagnosis. The resulting data-augmented diagnosis algorithm overcomes key problems in software diagnosis algorithms: ranking diagnoses and distinguishing between diagnoses with high probability and low probability. We demonstrate the efficiency of the proposed approach empirically on three open sources domains, showing significant increase in accuracy of diagnosis and efficiency of troubleshooting. These encouraging results suggests broader use of data-driven methods to complement and improve existing model-based methods.
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31

Mahich, Mahesh Kumar, Ghanshyam Rathi, and Mahendra Kumar Agrawal. "The Utility of Transbronchial Needle Aspiration and Conventional Diagnostic Procedures in the Diagnosis of Bronchogenic Carcinoma." Asian Journal of Medical Research 8, no. 3 (September 2019): TB01—TB05. http://dx.doi.org/10.21276/ajmr.2019.8.3.tb1.

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32

Pandey, Hari Shankar, Manoj Kumar Gupta, Ashima Pradhan, and Asha Agrawal. "Optical Spectroscopy as a Diagnostic Tool in Oropharyngeal Carcinoma & Its Correlation with Clinico-Histological Diagnosis." Indian Journal of Pathology: Research and Practice 5, no. 3 (2016): 317–23. http://dx.doi.org/10.21088/ijprp.2278.148x.5316.13.

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33

Mohammed Alanazi, Faheem, Ali Alyami, and Najd Mujawwil Alanazi. "Discrepancy between Hospital Discharge Diagnosis and Emergency Department Admission Diagnosis." Journal of Pharmaceutical Research International 35, no. 1 (January 29, 2023): 18–23. http://dx.doi.org/10.9734/jpri/2023/v35i17299.

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The objective is to investigate the matching between emergency department and discharge diagnosis as well as how investigations affect accurately of emergency department diagnosis. The study was conducted retrospectively over a six-month period. Setting: The emergency department Department at king Saud medical (KSMC), including four in-patient specialties: orthopedics, surgery, and medicine. Subjects: All patients that entered the emergency room during the study period. The correlation degree of hospital discharge diagnosis and admission diagnosis serve as the primary outcome markers. Results: 72% of diagnoses at admission completely or partially matched diagnoses at discharge. Young people, and traumatized cases had significantly superior diagnosis accuracy, according to data. The diagnostic accuracy was impacted by the specialization department and the investigations done. In conclusion, the physical examination and history are still the two most important diagnostic techniques employed in the emergency room. Simple tests available in the ER were frequently ineffective at improving diagnostic accuracy.
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34

Hu, He-xuan, Anne-Lise Gehin, and Mireille Bayart. "Relation between global diagnosis and diagnoses obtained from subsystems." IFAC Proceedings Volumes 42, no. 4 (2009): 379–84. http://dx.doi.org/10.3182/20090603-3-ru-2001.0308.

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35

Bond, Emily O., Jean Urick, and M. Kay M. Judge. "Nursing Diagnosis at Work: From Metaphors to Nursing Diagnoses." International Journal of Nursing Terminologies and Classifications 10, no. 2 (April 1999): 81–83. http://dx.doi.org/10.1111/j.1744-618x.1999.tb00030.x.

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36

Madan, NehaK, Shilpi Agarwal, Smita Singh, and Manjula Jain. "Pigmented basal cell carcinoma: Cytological diagnosis and differential diagnoses." Journal of Cytology 29, no. 4 (2012): 273. http://dx.doi.org/10.4103/0970-9371.103952.

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37

Halloran, Edward J. "Nursing workload, medical diagnosis related groups, and nursing diagnoses." Research in Nursing & Health 8, no. 4 (December 1985): 421–33. http://dx.doi.org/10.1002/nur.4770080415.

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38

Berg, Anne T., Shlomo Shinnar, Susan R. Levy, and Francine M. Testa. "Newly Diagnosed Epilepsy in Children: Presentation at Diagnosis." Epilepsia 40, no. 4 (April 1999): 445–52. http://dx.doi.org/10.1111/j.1528-1157.1999.tb00739.x.

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39

Stern, Roni, Meir Kalech, Alexander Feldman, and Gregory Provan. "Exploring the Duality in Conflict-Directed Model-Based Diagnosis." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 828–34. http://dx.doi.org/10.1609/aaai.v26i1.8231.

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A model-based diagnosis problem occurs when an observation is inconsistent with the assumption that the diagnosed system is not faulty. The task of a diagnosis engine is to compute diagnoses, which are assumptions on the health of components in the diagnosed system that explain the observation. In this paper, we extend Reiter's well-known theory of diagnosis by exploiting the duality of the relation between conflicts and diagnoses. This duality means that a diagnosis is a hitting set of conflicts, but a conflict is also a hitting set of diagnoses. We use this property to interleave the search for diagnoses and conflicts: a set of conflicts can guide the search for diagnosis, and the computed diagnoses can guide the search for more conflicts. We provide the formal basis for this dual conflict-diagnosis relation, and propose a novel diagnosis algorithm that exploits this duality. Experimental results show that the new algorithm is able to find a minimal cardinality diagnosis faster than the well-known Conflict-Directed A*.
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40

Nurjannah, Intansari, Dewi Retno Pamungkas, and Sri Warsini. "Perbandingan Antara Diagnosis yang Sering Ditegakkan dan Possible Diagnosis yang Diprediksikan oleh Perawat Pada Klien dengan Gangguan Jiwa." Jurnal Keperawatan Klinis dan Komunitas 1, no. 1 (October 16, 2017): 8. http://dx.doi.org/10.22146/jkkk.29011.

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Background: There is not enough information related to the accuracy of nursing and collaborative diagnoses established by nurses in psychiatric setting in Indonesia.Objective: The objective of this study was to identify the correspondence between nursing and collaborative diagnoses established and predicted by nurses.Methods: This was a descriptive cross-sectional study which employed 81 nurse respondents. Data were collected in 2013 using two types of questionnaires. The rst questionnaire was used to identify the most frequent nursing and collaborative diagnoses encountered by the nurses. The second questionnaire was used to identify data which were most frequently identi ed by the nurses. The second questionnaire was developed based on the sequence in the Intan’s Screening Diagnosis Assessment (ISDA).Results: The results indicated that there were 46 nursing diagnosis labels established by the nurses. Of the 46 nursing diagnosis labels, only 13 (28.26%) corresponded precisely to the labels in North American Nursing Diagnoses Association (NANDA) taxonomy (2012-2014) of nursing diagnoses. As many as 11 diagnoses (23.91%) could be included as key concepts (or diagnostic foci) in NANDA taxonomy. However, these nursing diagnosis labels did not written correctly as in NANDA labels. There were also 22 diagnosis (47%) labels not listed in NANDA taxonomy.Conclusion: The majority of nursing diagnosis labels did not match with nursing diagnosis labels in NANDA taxonomy. ABSTRAKLatar belakang: Belum banyak informasi terkait akurasi diagnosis keperawatan dan kolaboratif yang dibuat perawat dalam setting keperawatan jiwa di Indonesia.Tujuan: Tujuan dari peneltian ini untuk mengidenti kasi kesesuaian antara diagnosis keperawatan dan kolaboratif yang sudah ditegakkan dan yang diduga oleh perawat. Metode: Penelitian ini menggunakan rancangan cross sectional yang melibatkan 81 responden perawat. Data dikumpulkan pada tahun 2013 menggunakan 2 kuesioner. Kuesioner pertama digunakan untuk mengetahui diagnosis keperawatan dan kolaboratif yang paling sering ditegakkan oleh perawat. Kuesioner kedua digunakan untuk mengidenti kasi data yang paling sering ditemukan oleh perawat. Kuesioner kedua dikembangkan berdasarkan Intan’s Screening Diagnosis Assessment (ISDA).Hasil: Dari hasil penelitian didapati terdapat 46 label diagnosis keperawatan dibuat oleh perawat. Dari 46 label diagnosis keperawatan hanya 14 label diagnosis (28,26%) yang sesuai dengan label diagnosis berdasarkan taxonomi North American Nursing Diagnoses Association (NANDA) (2012-2014). Sebanyak 11 diagnosis (23,91%) dapat tercakup sebagai konsep penting (atau fokus diagnostik) dalam taksonomi NANDA. Namun label diagnosis keperawatan tersebut tidak dituliskan secara benar sesuai label NANDA. Selain itu ada juga 22 label diagnosis yang dituliskan tidak sesuai taksonomi NANDA.Kesimpulan: Mayoritas label diagnosis keperawatan yang dituliskan perawat tidak sesuai dengan label diagnosis keperawatan dalam taksonomi NANDA.
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41

Woolf, P. Grahame, John O'Shea, and Peter J. Davies. "Diagnosis." Musical Times 132, no. 1778 (April 1991): 196. http://dx.doi.org/10.2307/966139.

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42

Grieve, Gregory P. "Diagnosis." Physiotherapy Practice 4, no. 2 (January 1988): 73–77. http://dx.doi.org/10.3109/09593988809159054.

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43

Mazza, J. J. "Diagnosis?" Clinical Medicine & Research 2, no. 4 (November 1, 2004): 253. http://dx.doi.org/10.3121/cmr.2.4.253.

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44

Carson, Mike. "Diagnosis." Hopkins Review 2, no. 2 (2009): 231. http://dx.doi.org/10.1353/thr.0.0071.

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45

Rosenfeld, Richard M. "Diagnosis." Otolaryngology–Head and Neck Surgery 151, no. 1 (June 23, 2014): 1–3. http://dx.doi.org/10.1177/0194599814533287.

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46

DeMauro, Christopher A., and Mindy M. Horrow. "Diagnosis." Ultrasound Quarterly 24, no. 2 (June 2008): 121–23. http://dx.doi.org/10.1097/ruq.0b013e31817b62b8.

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47

VanSant, Ann F. "Diagnosis." Pediatric Physical Therapy 19, no. 2 (2007): 107. http://dx.doi.org/10.1097/pep.0b013e318057f77a.

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48

van Zwet, A. A., and Francis Megraud. "Diagnosis." Current Opinion in Gastroenterology 14, Supplement 1 (January 1998): S27—S33. http://dx.doi.org/10.1097/00001574-199801001-00007.

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49

van Zwet, A. A., and Francis Mégraud. "Diagnosis." Current Opinion in Gastroenterology 14 (January 1998): S27—S34. http://dx.doi.org/10.1097/00001574-199801031-00007.

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50

HINTON, JANINE E. "Diagnosis." Nursing Management (Springhouse) 28, no. 6 (June 1997): 41. http://dx.doi.org/10.1097/00006247-199706010-00011.

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