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Journal articles on the topic 'Clinical learning'

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Author: Grafiati
Published: 4 June 2021
Last updated: 20 February 2023

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1

Jones-Schenk, Jan. "Redesigning Clinical Learning." Journal of Continuing Education in Nursing 52, no. 9 (September 2021): 402–3. http://dx.doi.org/10.3928/00220124-20210804-03.

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2

Dovedi, Vishaal Kumar, and Anita Iyer. "Learning clinical leadership." Clinical Teacher 16, no. 3 (February 11, 2019): 290. http://dx.doi.org/10.1111/tct.13007.

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3

Carrion, C., P. Toran, A. Zamora, E. Balló, M. Quesada, A. Grau, A. Castro, et al. "Learning Clinical Communication." Procedia - Social and Behavioral Sciences 141 (August 2014): 85–89. http://dx.doi.org/10.1016/j.sbspro.2014.05.016.

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4

Ohno-Machado, Lucila. "Clinical machine learning." Journal of Biomedical Informatics 38, no. 5 (October 2005): 345–46. http://dx.doi.org/10.1016/j.jbi.2005.05.009.

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5

Pinnock, Ralph, and Paul Welch. "Learning clinical reasoning." Journal of Paediatrics and Child Health 50, no. 4 (December 23, 2013): 253–57. http://dx.doi.org/10.1111/jpc.12455.

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6

Rosen, Dennis. "Learning Clinical Reasoning." JAMA 303, no. 3 (January 20, 2010): 277. http://dx.doi.org/10.1001/jama.2009.2030.

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7

Ganiats, Theodore G. "Learning Clinical Reasoning." JAMA: The Journal of the American Medical Association 266, no. 22 (December 11, 1991): 3203. http://dx.doi.org/10.1001/jama.1991.03470220119044.

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8

Parsell, G., and J. Bligh. "Contract learning, clinical learning and clinicians." Postgraduate Medical Journal 72, no. 847 (May 1, 1996): 284–89. http://dx.doi.org/10.1136/pgmj.72.847.284.

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9

Corriero, Nicola, Pierpaolo Di Bitonto, Teresa Roselli, Veronica Rossano, and Enrica Pesare. "Simulations of Clinical Cases for Learning in e-Health." International Journal of Information and Education Technology 4, no. 4 (2014): 378–82. http://dx.doi.org/10.7763/ijiet.2014.v4.434.

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10

Lee, Cecilia S., and Aaron Y. Lee. "Clinical applications of continual learning machine learning." Lancet Digital Health 2, no. 6 (June 2020): e279-e281. http://dx.doi.org/10.1016/s2589-7500(20)30102-3.

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11

Bradley, Paul, and Keith Postlethwaite. "Simulation in clinical learning." Medical Education 37, s1 (November 2003): 1–5. http://dx.doi.org/10.1046/j.1365-2923.37.s1.1.x.

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Wasfy, Jason H. "Learning About Clinical Uncertainty." Academic Medicine 81, no. 12 (December 2006): 1075. http://dx.doi.org/10.1097/01.acm.0000242576.25803.65.

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13

Nordquist, Jonas, Jena Hall, Kelly Caverzagie, Linda Snell, Ming-Ka Chan, Brent Thoma, Saleem Razack, and Ingrid Philibert. "The clinical learning environment." Medical Teacher 41, no. 4 (March 17, 2019): 366–72. http://dx.doi.org/10.1080/0142159x.2019.1566601.

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14

Mary Ann Baily. "Learning from Clinical Experience." Hastings Center Report 38, no. 5 (2008): 3. http://dx.doi.org/10.1353/hcr.0.0052.

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15

Bryan, Jean M., and Rebecca S. Storey. "Clinical Experience-Based Learning." Journal of Physical Therapy Education 4, no. 1 (January 1990): 45. http://dx.doi.org/10.1097/00001416-199001000-00011.

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16

Sigsby, Linda M. "Perioperative Clinical Learning Experiences." AORN Journal 80, no. 3 (September 2004): 476–90. http://dx.doi.org/10.1016/s0001-2092(06)60539-5.

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17

Slotnick, Hank. "Learning in Clinical Practice." Journal of Veterinary Medical Education 30, no. 1 (March 2003): 47–49. http://dx.doi.org/10.3138/jvme.30.1.47.

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18

Cook, Michael J., and Helen L. Leathard. "Learning for clinical leadership." Journal of Nursing Management 12, no. 6 (November 2004): 436–44. http://dx.doi.org/10.1111/j.1365-2834.2004.00420.x.

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19

Chappell, Kathy. "The Clinical Learning Environment." JONA: The Journal of Nursing Administration 46, no. 1 (January 2016): 1–3. http://dx.doi.org/10.1097/nna.0000000000000284.

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20

Rohlfing, Katharina J. "Clinical Issues: Learning Prepositions." Perspectives on Language Learning and Education 12, no. 3 (October 2005): 13–17. http://dx.doi.org/10.1044/lle12.3.13.

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21

Shailer, Barbara. "Clinical learning environment audit." Nurse Education Today 10, no. 3 (June 1990): 220–27. http://dx.doi.org/10.1016/0260-6917(90)90029-p.

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22

Weiss, Kevin B., James P. Bagian, and Thomas J. Nasca. "The Clinical Learning Environment." JAMA 309, no. 16 (April 24, 2013): 1687. http://dx.doi.org/10.1001/jama.2013.1931.

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23

Shaikh, Ms Anjum, Ms Firdos Shaikh, and Mr Suhaib Ramzan Prof M. M. Patil. "Clinical Depression Detection Using Speech Feature With Machine Learning Approach." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (June 30, 2018): 1437–40. http://dx.doi.org/10.31142/ijtsrd14363.

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24

Papp, Inkeri, Marjatta Markkanen, and Mikaela von Bonsdorff. "Clinical environment as a learning environment: student nurses’ perceptions concerning clinical learning experiences." Nurse Education Today 23, no. 4 (May 2003): 262–68. http://dx.doi.org/10.1016/s0260-6917(02)00185-5.

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25

Li, Alice M. L. "Simulation-Based Clinical Skill Training to Promote Effective Clinical Learning with Simulation Evaluation Rubrics in Nursing Education." International Journal of Information and Education Technology 6, no. 3 (2016): 237–42. http://dx.doi.org/10.7763/ijiet.2016.v6.692.

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26

Kaliyangile, Benuis. "Student Nurse’s Clinical Learning Environment: Clinical Teachers’ Perspective." TEXILA INTERNATIONAL JOURNAL OF NURSING 6, no. 1 (April 30, 2020): 59–62. http://dx.doi.org/10.21522/tijnr.2015.06.01.art006.

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27

Hooper, James, John O'Connor, and Richard Cheesmar. "Learning clinical biochemistry using multimedia interactive clinical cases." Clinica Chimica Acta 248, no. 1 (April 1996): 119–23. http://dx.doi.org/10.1016/0009-8981(95)06272-6.

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28

DANISH, KHALID FAROOQ, and AZRA SAEED AWAN. "BEDSIDE LEARNING IN CLINICAL TRAINING;." Professional Medical Journal 15, no. 03 (March 10, 2008): 305–8. http://dx.doi.org/10.29309/tpmj/2008.15.03.2843.

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Objectives: To find out the learning preferences of clinical students forbedside learning. Design: cross-sectional, descriptive. Methods: The study was done on medical students of theclinical classes in different Medical Colleges in Rawalpindi, Pakistan. Both male and female students were included inthe study. All students were given a questionnaire consisting of 5 questions regarding their preferences for bedsidelearning. Open-ended comments were also invited. Results: A total of 227 students of clinical classes participated inthe study. Most preferred location for bedside learning was the ward (70%, N=158). Most preferred group size was 5(62%, N=140). For duration of bedside learning session most learners preferred 2 hours (59%, N=134). The opinionregarding the mode of case presentation was divided indecisively. Howevermost responders favored single presenter(28.6%, N=65). The preferred frequency of bedside learning sessions was ‘daily’ (49.7%, N=106). Conclusions:Learners in clinical classes prefer bedside teaching as a daily event. Their preferences indicate that the bedside learningpossesses a clinical relevance and offers contextual learning opportunity. Much remains to be learnt about the learners’preferences regarding instruction method in bedside learning.
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29

Lincoln, Michelle A., and Lindy L. McAllister. "Peer learning in clinical education." Medical Teacher 15, no. 1 (January 1993): 17–26. http://dx.doi.org/10.3109/01421599309029007.

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30

Harrison, Kathryn. "Learning Microbiology through Clinical Consultation." InnovAiT: Education and inspiration for general practice 12, no. 4 (September 15, 2017): 229. http://dx.doi.org/10.1177/1755738017717753.

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31

Badrick, Tony, Giuseppe Banfi, Andreas Bietenbeck, Mark A. Cervinski, Tze Ping Loh, and Ken Sikaris. "Machine Learning for Clinical Chemists." Clinical Chemistry 65, no. 11 (November 1, 2019): 1350–56. http://dx.doi.org/10.1373/clinchem.2019.307512.

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32

Cox, Ken. "Teaching and learning clinical perception." Medical Education 30, no. 2 (March 1996): 90–96. http://dx.doi.org/10.1111/j.1365-2923.1996.tb00725.x.

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33

Hull, Melodie. "Learning and teaching clinical writing." Medical Writing 22, no. 1 (March 2013): 29–33. http://dx.doi.org/10.1179/2047480612z.00000000083.

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34

Nehyba, Katrine, Susan Miller, Joanne Connaughton, and Barbara Singer. "Assessing student clinical learning experiences." Clinical Teacher 14, no. 4 (August 1, 2016): 247–50. http://dx.doi.org/10.1111/tct.12557.

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35

Kobayashi, Yoshinori, Akira Fujiki, and Kazutaka Aonuma. "Learning From Clinical Randomized Trials." Circulation Journal 73, no. 2 (2009): 229–30. http://dx.doi.org/10.1253/circj.cj-08-1090.

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36

Cracknell, Elizabeth. "Learning Opportunities in Clinical Practice." British Journal of Occupational Therapy 53, no. 4 (April 1990): 133. http://dx.doi.org/10.1177/030802269005300401.

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37

Pfeffer, Marc A. "Learning From Major Clinical Trials." Circulation 136, no. 23 (December 5, 2017): 2207–9. http://dx.doi.org/10.1161/circulationaha.117.023937.

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38

Stark, Patsy. "Clinical skills teaching and learning." Clinical Teacher 6, no. 3 (September 2009): 211–13. http://dx.doi.org/10.1111/j.1743-498x.2009.00303.x.

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39

Kassirer, Jerome P., and Richard I. Kopelman. "Learning Clinical Reasoning from Examples." Hospital Practice 24, no. 3 (March 15, 1989): 27–45. http://dx.doi.org/10.1080/21548331.1989.11703675.

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40

Leinster, Sam. "Learning in the clinical environment." Medical Teacher 31, no. 2 (January 2009): 79–81. http://dx.doi.org/10.1080/01421590902744936.

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41

Daley, Barbara J. "Learning in Clinical Nursing Practice." Holistic Nursing Practice 16, no. 1 (October 2001): 43–54. http://dx.doi.org/10.1097/00004650-200110000-00009.

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42

Williams Grad, Allison F., Sally Wellard, and Elizabeth Bethune. "Assessing Australian undergraduate clinical Learning." Collegian 8, no. 4 (January 2001): 9–13. http://dx.doi.org/10.1016/s1322-7696(08)60028-1.

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43

Doherty, Iain, and Judy McKimm. "e-learning in clinical teaching." British Journal of Hospital Medicine 71, no. 1 (January 2010): 44–47. http://dx.doi.org/10.12968/hmed.2010.71.1.45973.

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44

Kalkbrenner, Anne C., and Patricia A. Brandt. "Coaching Strategies for Clinical Learning." Nurse Educator 37, no. 5 (2012): 185–86. http://dx.doi.org/10.1097/nne.0b013e318262ab8a.

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45

Wilkerson, LuAnn. "Learning in a Clinical Setting." To Improve the Academy 4, no. 1 (June 1985): 120–33. http://dx.doi.org/10.1002/j.2334-4822.1985.tb00072.x.

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46

Warnat-Herresthal, Stefanie, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry, Sathyanarayanan Manamohan, Saikat Mukherjee, Vishesh Garg, Ravi Sarveswara, et al. "Swarm Learning for decentralized and confidential clinical machine learning." Nature 594, no. 7862 (May 26, 2021): 265–70. http://dx.doi.org/10.1038/s41586-021-03583-3.

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AbstractFast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.
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47

Plante, Elena, and Rebecca L. Gómez. "Learning Without Trying: The Clinical Relevance of Statistical Learning." Language, Speech, and Hearing Services in Schools 49, no. 3S (August 14, 2018): 710–22. http://dx.doi.org/10.1044/2018_lshss-stlt1-17-0131.

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Purpose Statistical learning research seeks to identify the means by which learners, with little perceived effort, acquire the complexities of language. In the past 50 years, numerous studies have uncovered powerful learning mechanisms that allow for learning within minutes of exposure to novel language input. Method We consider the value of information from statistical learning studies that show potential for making treatment of language disorders faster and more effective. Results Available studies include experimental research that demonstrates the conditions under which rapid learning is possible, research showing that these findings apply to individuals with disorders, and translational work that has applied learning principles in treatment and educational contexts. In addition, recent research on memory formation has implications for treatment of language deficits. Conclusion The statistical learning literature offers principles for learning that can improve clinical outcomes for children with language impairment. There is potential for further applications of this basic research that is yet unexplored.
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48

Zuhroidah, Ida, Nurul Huda, and Bagus Dwi Cahyono. "THE EFFECT OF CLINICAL TEACHING METHOD AND LEARNING STYLE ON CLINICAL NURSING LEARNING OUTCOMES." Nurse and Health: Jurnal Keperawatan 8, no. 2 (December 17, 2019): 108–14. http://dx.doi.org/10.36720/nhjk.v8i2.120.

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Background: Nursing Academy of Pasuruan has used problem solving method for learning clinical nursing practice. However, there is obstacle in the implementation of the method due to wide variation in implementing the method among field instructors. Theoretically, bedside teaching method can be used for learning activities to improve learning outcomes. Theoretically, students' learning style is associated with learning outcomes.Objective: This study aimed to examine the effect of clinical bedside teaching method and learning style of students on clinical practice outcome among nursing students at the Academy of Nursing.Method: The research method used Quasi-Experimental. The population source was students at the Academy of Nursing, Pasuruan. A sample of 80 students were selected by simple random sampling. Problem solving was used as a comparison method. The data were collected using standard questionnaires, and analyzed by multiple linear regression model.Result: Results indicated that bedside teaching resulted in higher clinical nursing learning outcome than problem solving method (b = 3.5, p < 0.001, CI 95% 2.6 to 4.4). There was no statistically significant effect of learning styles on learning outcomes of nursing clinical practice (p > 0.05).Conclusion: This study concludes that bedside teaching method results in better clinical nursing learning outcome than problem solving method. It is recommended that all faculty members use bedside teaching as the learning strategy to improve learning outcomes in clinical practice. Key words: Bedside Teaching, Problem Solving, Learning Styles, Clinical Practical Learning Outcomes.
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49

Jones, Woodson S., Stephen C. Maturo, and Lisa R. Hutcherson. "Get a “CLEW”: Using Clinical Learning Environment Walks (CLEWs) to Optimize Clinical Learning Environments." Journal of Graduate Medical Education 8, no. 3 (July 1, 2016): 458–59. http://dx.doi.org/10.4300/jgme-d-15-00620.1.

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50

Nielsen, Ann. "Concept-Based Learning in Clinical Experiences: Bringing Theory to Clinical Education for Deep Learning." Journal of Nursing Education 55, no. 7 (July 1, 2016): 365–71. http://dx.doi.org/10.3928/01484834-20160615-02.

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