Check health professions papers: citations, claims and retractions

The effect of fear of movement beliefs on pain and disability after surgery for lumbar and cervical degenerative conditions

Archer, K. R., Wegener, S. T., Seebach, C., Song, Y., Skolasky, R. L., Thornton, C., Khanna, A. J., & Riley, L. H. (2011) · Spine

Musculoskeletal pain and rehabilitationSpine and Intervertebral Disc Pathology

Cited by 95

Ill-defined and multiple causes on death certificates – A study of misclassification in mortality statistics

D'Amico, M., Agozzino, E., Biagino, A., Simonetti, A., & Marinelli, P. (1999) · European Journal of Epidemiology

Medical Coding and Health InformationAutopsy Techniques and Outcomes

Cited by 95

Systematic Review of Digital Interventions for Pediatric Asthma Management

Ramsey, R. R., Plevinsky, J. M., Kollin, S. R., Gibler, R. C., Guilbert, T. W., & Hommel, K. A. (2020) · The Journal of Allergy and Clinical Immunology: In Practice

Mobile Health and mHealth ApplicationsMedication Adherence and Compliance

Cited by 95

Participatory Methods to Engage Health Service Users in the Development of Electronic Health Resources: Systematic Review

Moore, G., Wilding, H., Gray, K., & Castle, D. (2019) · Journal of Participatory Medicine

Health Literacy and Information AccessibilityMobile Health and mHealth Applications

Cited by 95

Clinical Policy Recommendations from the VHA State-of-the-Art Conference on Non-Pharmacological Approaches to Chronic Musculoskeletal Pain

Kligler, B., Bair, M. J., Banerjea, R., DeBar, L., Ezeji-Okoye, S., Lisi, A., Murphy, J. L., Sandbrink, F., & Cherkin, D. C. (2018) · Journal of General Internal Medicine

Musculoskeletal pain and rehabilitationPain Management and Opioid Use

Cited by 95

Old-fashioned technology in the era of “bling”: is there a future for text messaging in health care?

Willcox, J. C., Dobson, R., & Whittaker, R. (2019) · Journal of Medical Internet Research

Mobile Health and mHealth ApplicationsMobile Learning in Education

Cited by 95

Climate Change–Related Water Disasters’ Impact on Population Health

Veenema, T. G., Thornton, C. P., Lavin, R. P., Bender, A. K., Seal, S., & Corley, A. (2017) · Journal of Nursing Scholarship

Disaster Response and ManagementClimate Change and Health Impacts

Cited by 95

A digital health intervention for cardiovascular disease management in primary care (CONNECT) randomized controlled trial

Redfern, J., Coorey, G., Mulley, J., Scaria, A., Neubeck, L., Hafiz, N., Pitt, C., Weir, K., Forbes, J., Parker, S., et al. (2020) · npj Digital Medicine

Mobile Health and mHealth ApplicationsDigital Mental Health Interventions

Cited by 95

Serum cortisol: an up-to-date assessment of routine assay performance

Hawley, J. M., Owen, L. J., Lockhart, S. J., Monaghan, P. J., Armston, A., Chadwick, C. A., Wilshaw, H., Freire, M., Perry, L., & Keevil, B. G. (2016) · Clinical Chemistry

Clinical Laboratory Practices and Quality ControlAdrenal Hormones and Disorders

Cited by 95

Long-term follow-up results of selective laryngeal adductor denervation– reinnervation surgery for adductor spasmodic dysphonia

Chhetri, D. K., Mendelsohn, A. H., Blumin, J. H., & Berke, G. S. (2006) · The Laryngoscope

Voice and Speech DisordersThyroid and Parathyroid Surgery

Cited by 95

'Treated as a number, not treated as a person': a qualitative exploration of the perceived barriers to effective pain management of patients with chronic pain

Hadi, M. A., Alldred, D. P., Briggs, M., Marczewski, K., & Closs, S. J. (2017) · BMJ Open

Musculoskeletal pain and rehabilitationPain Management and Opioid Use

Cited by 95

Effect of adherence to self-monitoring of diet and physical activity on weight loss in a technology-supported behavioral intervention

Wang, J., Sereika, S., Chasens, Ewing, Matthews, & Burke, L. (2012) · Patient Preference and Adherence

Mobile Health and mHealth ApplicationsBehavioral Health and Interventions

Cited by 95

Identification of important factors in an inpatient fall risk prediction model to improve the quality of care using EHR and electronic administrative data: A machine-learning approach

Lindberg, D. S., Prosperi, M., Bjarnadottir, R. I., Thomas, J., Crane, M., Chen, Z., Shear, K., Solberg, L. M., Snigurska, U. A., Wu, Y., et al. (2020) · International Journal of Medical Informatics

Balance, Gait, and Falls PreventionMachine Learning in Healthcare

Cited by 95

Psychometric properties of the Brief Pain Inventory among patients with osteoarthritis undergoing total hip replacement surgery

Kapstad, H., Rokne, B., & Stavem, K. (2010) · Health and Quality of Life Outcomes

Musculoskeletal pain and rehabilitationTotal Knee Arthroplasty Outcomes

Cited by 95

Health Care Provision for Osteoarthritis: Concordance between What Patients Would like and What Health Professionals Think They Should Have

Mann, C., & Gooberman‐Hill, R. (2011) · Arthritis Care & Research

Musculoskeletal pain and rehabilitationOsteoarthritis Treatment and Mechanisms

Cited by 95

Prediction of heart disease using multilayer perceptron neural network

Sonawane, J. S., & Patil, D. R. (2014) · International Conference on Information Communication and Embedded Systems (ICICES2014)

Artificial Intelligence in HealthcareData Mining and Machine Learning Applications

Cited by 94

Epidemiology of Chronic Pain in Denmark and Sweden

Harker, J., Reid, K. J., Bekkering, G. E., Kellen, E., Bala, M. M., Riemsma, R., Worthy, G., Misso, K., & Kleijnen, J. (2012) · Pain Research and Treatment

Musculoskeletal pain and rehabilitationPain Mechanisms and Treatments

Cited by 94

Stress symptoms and burnout in obstetric and gynaecology residents

Castelo‐Branco, C., Figueras, F., Eixarch, E., Quereda, F., Cancelo, M., González, S., & Balasch, J. (2007) · BJOG: An International Journal of Obstetrics & Gynaecology

Healthcare professionals’ stress and burnoutStress and Burnout Research

Cited by 94

Evaluating the risk of type 2 diabetes mellitus using artificial neural network: An effective classification approach

Wang, C., Li, L., Wang, L., Ping, Z., Flory, M. T., Wang, G., Xi, Y., & Li, W. (2013) · Diabetes Research and Clinical Practice

Artificial Intelligence in HealthcareDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 94

The complex case of EHRs: examining the factors impacting the EHR user experience

Tutty, M. A., Carlasare, L. E., Lloyd, S., & Sinsky, C. A. (2019) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 94

Interpretive Diagnostic Error Reduction in Surgical Pathology and Cytology: Guideline From the College of American Pathologists Pathology and Laboratory Quality Center and the Association of Directors of Anatomic and Surgical Pathology

Nakhleh, R. E., Nosé, V., Colasacco, C., Fatheree, L. A., Lillemoe, T. J., McCrory, D. C., Meier, F. A., Otis, C. N., Owens, S. R., Raab, S. S., et al. (2016) · Archives of Pathology & Laboratory Medicine

Clinical Laboratory Practices and Quality ControlClinical Reasoning and Diagnostic Skills

Cited by 94

Prevalence and relationship between burnout and depression in our future doctors: a cross-sectional study in a cohort of preclinical and clinical medical students in Ireland

Fitzpatrick, O., Biesma, R., Conroy, R. M., & McGarvey, A. (2019) · BMJ Open

Healthcare professionals’ stress and burnoutStress and Burnout Research

Cited by 94

Video-Game–Based Exercises for Older People With Chronic Low Back Pain: A Randomized Controlledtable Trial (GAMEBACK)

Zadro, J. R., Shirley, D., Simic, M., Mousavi, S. J., Ceprnja, D., Maka, K., Sung, J., & Ferreira, P. (2019) · Physical Therapy

Musculoskeletal pain and rehabilitationPhysical Activity and Health

Cited by 94

Glucose meter performance criteria for tight glycemic control estimated by simulation modeling

Karon, B. S., Boyd, J. C., & Klee, G. G. (2010) · Clinical Chemistry

Clinical Laboratory Practices and Quality ControlHyperglycemia and glycemic control in critically ill and hospitalized patients

Cited by 94