Published on in Vol 7, No 3 (2019): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10010, first published .
Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review

Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review

Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review

Journals

  1. Powell J. Trust Me, I’m a Chatbot: How Artificial Intelligence in Health Care Fails the Turing Test. Journal of Medical Internet Research 2019;21(10):e16222 View
  2. Ye R, Zhou X, Shao F, Xiong L, Hong J, Huang H, Tong W, Wang J, Chen S, Cui A, Peng C, Zhao Y, Chen L. Feasibility of a 5G-Based Robot-Assisted Remote Ultrasound System for Cardiopulmonary Assessment of Patients With Coronavirus Disease 2019. Chest 2021;159(1):270 View
  3. Shen J, Chen J, Zheng Z, Zheng J, Liu Z, Song J, Wong S, Wang X, Huang M, Fang P, Jiang B, Tsang W, He Z, Liu T, Akinwunmi B, Wang C, Zhang C, Huang J, Ming W. An Innovative Artificial Intelligence–Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study. Journal of Medical Internet Research 2020;22(9):e21573 View
  4. Dallora A, Kvist O, Berglund J, Ruiz S, Boldt M, Flodmark C, Anderberg P. Chronological Age Assessment in Young Individuals Using Bone Age Assessment Staging and Nonradiological Aspects: Machine Learning Multifactorial Approach. JMIR Medical Informatics 2020;8(9):e18846 View
  5. Dallora A, Berglund J, Brogren M, Kvist O, Diaz Ruiz S, Dübbel A, Anderberg P. Age Assessment of Youth and Young Adults Using Magnetic Resonance Imaging of the Knee: A Deep Learning Approach. JMIR Medical Informatics 2019;7(4):e16291 View
  6. Wolff J, Pauling J, Keck A, Baumbach J. Systematic Review of Economic Impact Studies of Artificial Intelligence in Health Care. Journal of Medical Internet Research 2020;22(2):e16866 View
  7. Magagna W, Wang N, Peck K. Current and Future Trends in Life Sciences Training: Questionnaire Study. JMIR Medical Education 2020;6(1):e15877 View
  8. Li S, Wang Z, Visser L, Wisner E, Cheng H. Pilot study: Application of artificial intelligence for detecting left atrial enlargement on canine thoracic radiographs. Veterinary Radiology & Ultrasound 2020;61(6):611 View
  9. Iqbal U, Celi L, Li Y. How Can Artificial Intelligence Make Medicine More Preemptive?. Journal of Medical Internet Research 2020;22(8):e17211 View
  10. Nahmias D, Civillico E, Kontson K. Deep learning and feature based medication classifications from EEG in a large clinical data set. Scientific Reports 2020;10(1) View
  11. Al-Dury N, Ravn-Fischer A, Hollenberg J, Israelsson J, Nordberg P, Strömsöe A, Axelsson C, Herlitz J, Rawshani A. Identifying the relative importance of predictors of survival in out of hospital cardiac arrest: a machine learning study. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine 2020;28(1) View
  12. Javaid M, Haleem A, Khan I, Vaishya R, Vaish A. Extending capabilities of artificial intelligence for decision-making and healthcare education. Apollo Medicine 2020;17(1):53 View
  13. Kim H. Decision-Making in Artificial Intelligence: Is It Always Correct?. Journal of Korean Medical Science 2020;35(1) View
  14. Meskó B. The Real Era of the Art of Medicine Begins with Artificial Intelligence. Journal of Medical Internet Research 2019;21(11):e16295 View
  15. Campagner A, Ciucci D, Svensson C, Figge M, Cabitza F. Ground truthing from multi-rater labeling with three-way decision and possibility theory. Information Sciences 2021;545:771 View
  16. Tanut B, Riyamongkol P. The Development of a Defect Detection Model from the High-Resolution Images of a Sugarcane Plantation Using an Unmanned Aerial Vehicle. Information 2020;11(3):136 View
  17. Zhou J, Zeng Z, Li L. <p>Progress of Artificial Intelligence in Gynecological Malignant Tumors</p>. Cancer Management and Research 2020;Volume 12:12823 View
  18. Corbella S, Srinivas S, Cabitza F. Applications of deep learning in dentistry. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology 2021;132(2):225 View
  19. Kim H, Lee Y, Kim Y, Lim Y, Lee J, Woo J, Jang S, Oh Y, Kim H, Lee E, Kang D, Kim K. Deep Learning-Based Method to Differentiate Neuromyelitis Optica Spectrum Disorder From Multiple Sclerosis. Frontiers in Neurology 2020;11 View
  20. El-bana S, Al-Kabbany A, Sharkas M. A multi-task pipeline with specialized streams for classification and segmentation of infection manifestations in COVID-19 scans. PeerJ Computer Science 2020;6:e303 View
  21. Jussupow E, Spohrer K, Heinzl A, Gawlitza J. Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence. Information Systems Research 2021;32(3):713 View
  22. Hashmani M, Jameel S, Rizvi S, Shukla S. An Adaptive Federated Machine Learning-Based Intelligent System for Skin Disease Detection: A Step toward an Intelligent Dermoscopy Device. Applied Sciences 2021;11(5):2145 View
  23. Campbell J, Mathenge C, Cherwek H, Balaskas K, Pasquale L, Keane P, Chiang M. Artificial Intelligence to Reduce Ocular Health Disparities: Moving From Concept to Implementation. Translational Vision Science & Technology 2021;10(3):19 View
  24. Lennox-Chhugani N, Chen Y, Pearson V, Trzcinski B, James J. Women’s attitudes to the use of AI image readers: a case study from a national breast screening programme. BMJ Health & Care Informatics 2021;28(1):e100293 View
  25. Haleem A, Javaid M, Singh R, Suman R. Applications of Artificial Intelligence (AI) for cardiology during COVID-19 pandemic. Sustainable Operations and Computers 2021;2:71 View
  26. Yin J, Ngiam K, Teo H. Role of Artificial Intelligence Applications in Real-Life Clinical Practice: Systematic Review. Journal of Medical Internet Research 2021;23(4):e25759 View
  27. Drummond D. Between competence and warmth: the remaining place of the physician in the era of artificial intelligence. npj Digital Medicine 2021;4(1) View
  28. Rasmy L, Xiang Y, Xie Z, Tao C, Zhi D. Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction. npj Digital Medicine 2021;4(1) View
  29. Fehrenbach U, Xin S, Hartenstein A, Auer T, Dräger F, Froböse K, Jann H, Mogl M, Amthauer H, Geisel D, Denecke T, Wiedenmann B, Penzkofer T. Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI—A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making. Cancers 2021;13(11):2726 View
  30. Cabitza F, Campagner A. The need to separate the wheat from the chaff in medical informatics. International Journal of Medical Informatics 2021;153:104510 View
  31. Saheb T, Saheb T, Carpenter D. Mapping research strands of ethics of artificial intelligence in healthcare: A bibliometric and content analysis. Computers in Biology and Medicine 2021;135:104660 View
  32. Erne F, Dehncke D, Herath S, Springer F, Pfeifer N, Eggeling R, Küper M. Deep Learning in the Detection of Rare Fractures – Development of a “Deep Learning Convolutional Network” Model for Detecting Acetabular Fractures. Zeitschrift für Orthopädie und Unfallchirurgie 2023;161(01):42 View
  33. Arslan A, Cooper C, Khan Z, Golgeci I, Ali I. Artificial intelligence and human workers interaction at team level: a conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower 2022;43(1):75 View
  34. Nasseef O, Baabdullah A, Alalwan A, Lal B, Dwivedi Y. Artificial intelligence-based public healthcare systems: G2G knowledge-based exchange to enhance the decision-making process. Government Information Quarterly 2022;39(4):101618 View
  35. Huang J, Galal G, Etemadi M, Vaidyanathan M. Evaluation and Mitigation of Racial Bias in Clinical Machine Learning Models: Scoping Review. JMIR Medical Informatics 2022;10(5):e36388 View
  36. Li J, Zhou L, Zhan Y, Xu H, Zhang C, Shan F, Liu L. How does the artificial intelligence-based image-assisted technique help physicians in diagnosis of pulmonary adenocarcinoma? A randomized controlled experiment of multicenter physicians in China. Journal of the American Medical Informatics Association 2022;29(12):2041 View
  37. Quazi S, Saha R, Singh M. Applications of Artificial Intelligence in Healthcare. Journal of Experimental Biology and Agricultural Sciences 2022;10(1):211 View
  38. Jha S, Marina N, Wang J, Ahmad Z. A hybrid machine learning approach of fuzzy-rough-k-nearest neighbor, latent semantic analysis, and ranker search for efficient disease diagnosis. Journal of Intelligent & Fuzzy Systems 2022;42(3):2549 View
  39. Xu Q, Xie W, Liao B, Hu C, Qin L, Yang Z, Xiong H, Lyu Y, Zhou Y, Luo A, Li C. Interpretability of Clinical Decision Support Systems Based on Artificial Intelligence from Technological and Medical Perspective: A Systematic Review. Journal of Healthcare Engineering 2023;2023:1 View
  40. Aljameel S. A Proactive Explainable Artificial Neural Network Model for the Early Diagnosis of Thyroid Cancer. Computation 2022;10(10):183 View
  41. Zhang J, Budhdeo S, William W, Cerrato P, Shuaib H, Sood H, Ashrafian H, Halamka J, Teo J. Moving towards vertically integrated artificial intelligence development. npj Digital Medicine 2022;5(1) View
  42. Torrent-Sellens J, Jiménez-Zarco A, Saigí-Rubió F. Do People Trust in Robot-Assisted Surgery? Evidence from Europe. International Journal of Environmental Research and Public Health 2021;18(23):12519 View
  43. Hah H, Goldin D. Moving toward AI-assisted decision-making: Observation on clinicians’ management of multimedia patient information in synchronous and asynchronous telehealth contexts. Health Informatics Journal 2022;28(1):146045822210770 View
  44. Hah H, Goldin D. How Clinicians Perceive Artificial Intelligence–Assisted Technologies in Diagnostic Decision Making: Mixed Methods Approach. Journal of Medical Internet Research 2021;23(12):e33540 View
  45. Germain P, Vardazaryan A, Padoy N, Labani A, Roy C, Schindler T, El Ghannudi S. Deep Learning Supplants Visual Analysis by Experienced Operators for the Diagnosis of Cardiac Amyloidosis by Cine-CMR. Diagnostics 2021;12(1):69 View
  46. Raimondo D, Raffone A, Aru A, Giorgi M, Giaquinto I, Spagnolo E, Travaglino A, Galatolo F, Cimino M, Lenzi J, Centini G, Lazzeri L, Mollo A, Seracchioli R, Casadio P. Application of Deep Learning Model in the Sonographic Diagnosis of Uterine Adenomyosis. International Journal of Environmental Research and Public Health 2023;20(3):1724 View
  47. Yu Z, Zhang X, Lv H. Artificial Intelligence Imaging to Observe the Protective Effect of Hydrogen Sulfide on Acute Kidney Injury Caused by Urinary Sepsis. Journal of Sensors 2021;2021:1 View
  48. Wang L, Zhang Y, Wang D, Tong X, Liu T, Zhang S, Huang J, Zhang L, Chen L, Fan H, Clarke M. Artificial Intelligence for COVID-19: A Systematic Review. Frontiers in Medicine 2021;8 View
  49. Martinez-Millana A, Saez-Saez A, Tornero-Costa R, Azzopardi-Muscat N, Traver V, Novillo-Ortiz D. Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews. International Journal of Medical Informatics 2022;166:104855 View
  50. Chen M, Tan X, Padman R. A Machine Learning Approach to Support Urgent Stroke Triage Using Administrative Data and Social Determinants of Health at Hospital Presentation: Retrospective Study. Journal of Medical Internet Research 2023;25:e36477 View
  51. Sukegawa S, Tanaka F, Hara T, Yoshii K, Yamashita K, Nakano K, Takabatake K, Kawai H, Nagatsuka H, Furuki Y. Deep learning model for analyzing the relationship between mandibular third molar and inferior alveolar nerve in panoramic radiography. Scientific Reports 2022;12(1) View
  52. Lazzarini N, Filippoupolitis A, Manzione P, Eleftherohorinou H, Mansur A. A machine learning model on Real World Data for predicting progression to Acute Respiratory Distress Syndrome (ARDS) among COVID-19 patients. PLOS ONE 2022;17(7):e0271227 View
  53. Kriza C, Amenta V, Zenié A, Panidis D, Chassaigne H, Urbán P, Holzwarth U, Sauer A, Reina V, Griesinger C. Artificial intelligence for imaging-based COVID-19 detection: Systematic review comparing added value of AI versus human readers. European Journal of Radiology 2021;145:110028 View
  54. Suppakitjanusant P, Sungkanuparph S, Wongsinin T, Virapongsiri S, Kasemkosin N, Chailurkit L, Ongphiphadhanakul B. Identifying individuals with recent COVID-19 through voice classification using deep learning. Scientific Reports 2021;11(1) View
  55. Kang H, Kang J, Lee S, Sim H. Applications and Performances of Artificial Intelligence in Assessment and Diagnosis of Communication Disorders: A Systematic Review of the Literatures. Communication Sciences & Disorders 2022;27(3):703 View
  56. Campagner A, Sternini F, Cabitza F. Decisions are not all equal—Introducing a utility metric based on case-wise raters’ perceptions. Computer Methods and Programs in Biomedicine 2022;221:106930 View
  57. Droppelmann G, Tello M, García N, Greene C, Jorquera C, Feijoo F. Lateral elbow tendinopathy and artificial intelligence: Binary and multilabel findings detection using machine learning algorithms. Frontiers in Medicine 2022;9 View
  58. Jussupow E, Spohrer K, Heinzl A. Radiologists’ Usage of Diagnostic AI Systems. Business & Information Systems Engineering 2022;64(3):293 View
  59. Yu J, Hong S, Lee Y, Lee K, Lee I, Seo Y, Kang M, Kim K, Cha W, Shin S. Stakeholders’ Requirements for Artificial Intelligence for Healthcare in Korea. Healthcare Informatics Research 2022;28(2):143 View
  60. Jussupow E, Spohrer K, Heinzl A. Identity Threats as a Reason for Resistance to Artificial Intelligence: Survey Study With Medical Students and Professionals. JMIR Formative Research 2022;6(3):e28750 View
  61. Yuan D, Liu Y, Xu Z, Zhan Y, Chen J, Lukasiewicz T. Painless and accurate medical image analysis using deep reinforcement learning with task-oriented homogenized automatic pre-processing. Computers in Biology and Medicine 2023;153:106487 View
  62. Codlin A, Dao T, Vo L, Forse R, Van Truong V, Dang H, Nguyen L, Nguyen H, Nguyen N, Sidney-Annerstedt K, Squire B, Lönnroth K, Caws M. Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis. Scientific Reports 2021;11(1) View
  63. Yang K, Chen J, Wu H, Tian H, Ye X, Xu J, Luo X, Dong F. S-Thyroid Computer-Aided Diagnosis Ultrasound System of Thyroid Nodules: Correlation Between Transverse and Longitudinal Planes. Frontiers in Physiology 2022;13 View
  64. Kawai K, Uji A, Murakami T, Kadomoto S, Oritani Y, Dodo Y, Muraoka Y, Akagi T, Miyata M, Tsujikawa A. IMAGE EVALUATION OF ARTIFICIAL INTELLIGENCE–SUPPORTED OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IMAGING USING OCT-A1 DEVICE IN DIABETIC RETINOPATHY. Retina 2021;41(8):1730 View
  65. Obwegeser D, Timofte R, Mayer C, Eliades T, Bornstein M, Schätzle M, Patcas R. Using artificial intelligence to determine the influence of dental aesthetics on facial attractiveness in comparison to other facial modifications. European Journal of Orthodontics 2022;44(4):445 View
  66. Fritzsche M, Akyüz K, Cano Abadía M, McLennan S, Marttinen P, Mayrhofer M, Buyx A. Ethical layering in AI-driven polygenic risk scores—New complexities, new challenges. Frontiers in Genetics 2023;14 View
  67. Zhang X, Xie Z, Xiang Y, Baig I, Kozman M, Stender C, Giancardo L, Tao C. Issues in Melanoma Detection: Semisupervised Deep Learning Algorithm Development via a Combination of Human and Artificial Intelligence. JMIR Dermatology 2022;5(4):e39113 View
  68. Salama A, Ragab D, Abdel-Moneim N. Urban spaces as a positive catalyst during pandemics: Assessing the community’s well-being by using artificial intelligence techniques. Ain Shams Engineering Journal 2023;14(5):102084 View
  69. Kordi M, Dehghan M, Shayesteh A, Azizi A. The impact of artificial intelligence algorithms on management of patients with irritable bowel syndrome: A systematic review. Informatics in Medicine Unlocked 2022;29:100891 View
  70. Kumar R, Khan F, Sharma A, Aziz I, Poddar N. Recent Applications of Artificial Intelligence in the Detection of Gastrointestinal, Hepatic and Pancreatic Diseases. Current Medicinal Chemistry 2022;29(1):66 View
  71. Ramos M, Gomes D, Mello N, Silva E, Barreto J, Shimizu H. Big Data e Inteligência Artificial para pesquisa translacional na Covid-19: revisão rápida. Saúde em Debate 2022;46(135):1202 View
  72. Benlian A, Wiener M, Cram W, Krasnova H, Maedche A, Möhlmann M, Recker J, Remus U. Algorithmic Management. Business & Information Systems Engineering 2022;64(6):825 View
  73. Hariry R, Barenji R, Paradkar A. Towards Pharma 4.0 in clinical trials: A future-orientated perspective. Drug Discovery Today 2022;27(1):315 View
  74. Rösler W, Altenbuchinger M, Baeßler B, Beissbarth T, Beutel G, Bock R, von Bubnoff N, Eckardt J, Foersch S, Loeffler C, Middeke J, Mueller M, Oellerich T, Risse B, Scherag A, Schliemann C, Scholz M, Spang R, Thielscher C, Tsoukakis I, Kather J. An overview and a roadmap for artificial intelligence in hematology and oncology. Journal of Cancer Research and Clinical Oncology 2023;149(10):7997 View
  75. Delgado-Enales I, Del Ser J, Molina-Costa P. A framework to improve urban accessibility and environmental conditions in age-friendly cities using graph modeling and multi-objective optimization. Computers, Environment and Urban Systems 2023;102:101966 View
  76. Azevedo N, Kehayia E, Jarema G, Le Dorze G, Beaujard C, Yvon M. How artificial intelligence (AI) is used in aphasia rehabilitation: A scoping review. Aphasiology 2024;38(2):305 View
  77. Sharma M, Sharma S. Transforming Maritime Health with ChatGPT-Powered Healthcare Services for Mariners. Annals of Biomedical Engineering 2023;51(6):1123 View
  78. Nuutinen M, Leskelä R. Systematic Review of the Performance Evaluation of Clinicians with or without the Aid of Clinical Decision Support System. SSRN Electronic Journal 2023 View
  79. Fauzi A, Yueniwati Y, Naba A, Rahayu R. Performance of deep learning in classifying malignant primary and metastatic brain tumors using different MRI sequences: A medical analysis study. Journal of X-Ray Science and Technology 2023;31(5):893 View
  80. Sun K, Zheng X, Liu W. Increasing clinical medical service satisfaction: An investigation into the impacts of Physicians’ use of clinical decision-making support AI on patients’ service satisfaction. International Journal of Medical Informatics 2023;176:105107 View
  81. Das N, Happaerts S, Gyselinck I, Staes M, Derom E, Brusselle G, Burgos F, Contoli M, Dinh-Xuan A, Franssen F, Gonem S, Greening N, Haenebalcke C, Man W, Moisés J, Peché R, Poberezhets V, Quint J, Steiner M, Vanderhelst E, Abdo M, Topalovic M, Janssens W. Collaboration between explainable artificial intelligence and pulmonologists improves the accuracy of pulmonary function test interpretation. European Respiratory Journal 2023;61(5):2201720 View
  82. Guo W, Lv C, Guo M, Zhao Q, Yin X, Zhang L. Innovative Applications of Artificial Intelligence in Zoonotic Disease Management. Science in One Health 2023:100045 View
  83. Bonny T, Al Nassan W, Obaideen K, Al Mallahi M, Mohammad Y, El-damanhoury H. Contemporary Role and Applications of Artificial Intelligence in Dentistry. F1000Research 2023;12:1179 View
  84. Harris J. An AI-Enhanced Electronic Health Record Could Boost Primary Care Productivity. JAMA 2023;330(9):801 View
  85. Rostami M, Jalilian M. Artificial Intelligence and Its Potential Applications to Combat the COVID-19 Pandemic. Shiraz E-Medical Journal 2023;In Press(In Press) View
  86. Subramanian T, Shahi P, Araghi K, Mayaan O, Amen T, Iyer S, Qureshi S. Using Artificial Intelligence to Answer Common Patient-Focused Questions in Minimally Invasive Spine Surgery. Journal of Bone and Joint Surgery 2023;105(20):1649 View
  87. He H, Chen C, Zhang W, Wang Z, Zhang X. Body condition scoring network based on improved YOLOX. Pattern Analysis and Applications 2023;26(3):1071 View
  88. Shamszare H, Choudhury A. Clinicians’ Perceptions of Artificial Intelligence: Focus on Workload, Risk, Trust, Clinical Decision Making, and Clinical Integration. Healthcare 2023;11(16):2308 View
  89. Koh R, Khan M, Rashidiani S, Hassan S, Tucci V, Liu T, Nesovic K, Kumbhare D, Doyle T. Check It Before You Wreck It: A Guide to STAR-ML for Screening Machine Learning Reporting in Research. IEEE Access 2023;11:101567 View
  90. Poirier A, Riaño Moreno R, Takaindisa L, Carpenter J, Mehat J, Haddon A, Rohaim M, Williams C, Burkhart P, Conlon C, Wilson M, McClumpha M, Stedman A, Cordoni G, Branavan M, Tharmakulasingam M, Chaudhry N, Locker N, Fernando A, Balachandran W, Bullen M, Collins N, Rimer D, Horton D, Munir M, La Ragione R. VIDIIA Hunter: a low-cost, smartphone connected, artificial intelligence-assisted COVID-19 rapid diagnostic platform approved for medical use in the UK. Frontiers in Molecular Biosciences 2023;10 View
  91. Herington J, McCradden M, Creel K, Boellaard R, Jones E, Jha A, Rahmim A, Scott P, Sunderland J, Wahl R, Zuehlsdorff S, Saboury B. Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance. Journal of Nuclear Medicine 2023;64(10):1509 View
  92. Nuutinen M, Leskelä R. Systematic review of the performance evaluation of clinicians with or without the aid of machine learning clinical decision support system. Health and Technology 2023;13(4):557 View
  93. Oldfield M. Technical challenges and perception: does AI have a PR issue?. AI and Ethics 2023 View
  94. Herington J, McCradden M, Creel K, Boellaard R, Jones E, Jha A, Rahmim A, Scott P, Sunderland J, Wahl R, Zuehlsdorff S, Saboury B. Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation. Journal of Nuclear Medicine 2023;64(12):1848 View
  95. Dang A, Dang D, Vallish B. Extent of use of artificial intelligence & machine learning protocols in cancer diagnosis. Indian Journal of Medical Research 2023;157(1):11 View
  96. Watanabe M, Eguchi A, Sakurai K, Yamamoto M, Mori C, Kamijima M, Yamazakii S, Ohya Y, Kishi R, Yaegashi N, Hashimoto K, Ito S, Yamagata Z, Inadera H, Nakayama T, Sobue T, Shima M, Kageyama S, Suganuma N, Ohga S, Katoh T. Prediction of gestational diabetes mellitus using machine learning from birth cohort data of the Japan Environment and Children's Study. Scientific Reports 2023;13(1) View
  97. Abdollahifard S, Farrokhi A, Mowla A. Response to ‘Application of deep learning models for detection of subdural hematoma: a systematic review and meta-analysis’. Journal of NeuroInterventional Surgery 2023;15(10):1057 View
  98. Singareddy S, SN V, Jaramillo A, Yasir M, Iyer N, Hussein S, Nath T. Artificial Intelligence and Its Role in the Management of Chronic Medical Conditions: A Systematic Review. Cureus 2023 View
  99. Malinverno L, Barros V, Ghisoni F, Visonà G, Kern R, Nickel P, Ventura B, Šimić I, Stryeck S, Manni F, Ferri C, Jean-Quartier C, Genga L, Schweikert G, Lovrić M, Rosen-Zvi M. A historical perspective of biomedical explainable AI research. Patterns 2023;4(9):100830 View
  100. Vasile C, Iriart X. Embracing AI: The Imperative Tool for Echo Labs to Stay Ahead of the Curve. Diagnostics 2023;13(19):3137 View
  101. Koh B, Danpanichkul P, Wang M, Tan D, Ng C. Application of artificial intelligence in the diagnosis of hepatocellular carcinoma. eGastroenterology 2023;1(2):e100002 View
  102. Orfanoudaki A, Saghafian S, Song K, Chakkera H, Cook C. Algorithm, Human, or the Centaur: How to Enhance Clinical Care?. SSRN Electronic Journal 2022 View
  103. Liu C, Jiao D, Liu Z. Artificial Intelligence (AI)-aided Disease Prediction. BIO Integration 2020;1(3) View
  104. Chorney W, Wang H. Towards federated transfer learning in electrocardiogram signal analysis. Computers in Biology and Medicine 2024;170:107984 View
  105. Zhang Y, Stayt L, Sutherland S, Greenway K. How clinicians make decisions for patient management plans in telehealth. Journal of Advanced Nursing 2024 View
  106. Ciftci R, Secgin Y, Oner Z, Toy S, Oner S. Age Estimation Using Machine Learning Algorithms with Parameters Obtained from X-ray Images of the Calcaneus. Nigerian Journal of Clinical Practice 2024;27(2):209 View

Books/Policy Documents

  1. Holowka E, Woods S, Pahayahay A, Roy M, Khalili-Mahani N. Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. AI, Product and Service. View
  2. Campagner A, Conte E, Cabitza F. Machine Learning and Knowledge Extraction. View
  3. Lee T, Puyol-Antón E, Ruijsink B, Shi M, King A. Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers. View
  4. Karwasra R, Khanna K, Sharma N, Malhotra R, Sharma S, Singh S, Ali A, Verma S. Nature-Inspired Intelligent Computing Techniques in Bioinformatics. View
  5. Hassan A. Future of Organizations and Work After the 4th Industrial Revolution. View
  6. Pinto C, Faria J, Macedo L. Progress in Artificial Intelligence. View
  7. Xie S, Chen Y, Sun M, Ji S, Lu G, Li R, Wang M, Liu H, Zhang H. Proceedings of the 12th International Conference on Computer Engineering and Networks. View
  8. Avila-Ponce de León U, Vazquez-Jimenez A, Cervera A, Resendis-González G, Neri-Rosario D, Resendis-Antonio O. Application of Omic Techniques to Identify New Biomarkers and Drug Targets for COVID-19. View
  9. Wanis M, Yi W. Pharmaceutical Care in Digital Revolution. View
  10. Wrench J, Elmoudden S. The Role of Generative AI in the Communication Classroom. View