A Cardiac Deep Learning Model (CDLM) to Predict and Identify the Risk Factor of Congenital Heart Disease.
Prabu Pachiyannan et al. Diagnostics (Basel) 2023 13(13)

Artificial intelligence in the neonatal intensive care unit: the time is now.
Kristyn Beam et al. J Perinatol 2023

Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning-Based Text-Mining Approach.
Danila Azzolina et al. JMIR Public Health Surveill 2023 9e44467

Explainable machine learning model for predicting skeletal muscle loss during surgery and adjuvant chemotherapy in ovarian cancer.
Wen-Han Hsu et al. J Cachexia Sarcopenia Muscle 2023

Calibration and Validation of the Colorectal Cancer and Adenoma Incidence and Mortality (CRC-AIM) Microsimulation Model Using Deep Neural Networks.
Vahab Vahdat et al. Med Decis Making 2023 272989X231184175

Real-time Detection of Bladder Cancer Using Augmented Cystoscopy with Deep Learning: a Pilot Study.
Timothy Chan Chang et al. J Endourol 2023

Diagnostic performance of augmented intelligence with 2D and 3D total body photography and convolutional neural networks in a high-risk population for melanoma under real-world conditions: A new era of skin cancer screening?
Sara E Cerminara et al. Eur J Cancer 2023 190112954

Inferring cancer disease response from radiology reports using large language models with data augmentation and prompting.
Ryan Shea Ying Cong Tan et al. J Am Med Inform Assoc 2023

Value of the application of computed tomography-based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer.
Situ Xiong et al. Cancer Med 2023

Neural network-based method to stratify people at risk for developing diabetic foot: A support system for health professionals.
Ana Cláudia Barbosa Honório Ferreira et al. PLoS One 2023 18(7) e0288466

Efficacy of artificial intelligence in the detection of periodontal bone loss and classification of periodontal diseases: A systematic review.
Shankargouda Patil et al. J Am Dent Assoc 2023

AI-Human Hybrid Workflow Enhances Teleophthalmology for the Detection of Diabetic Retinopathy.
Eliot R Dow et al. Ophthalmol Sci 2023 3(4) 100330

Machine learning using multimodal clinical, electroencephalographic, and magnetic resonance imaging data can predict incident depression in adults with epilepsy: A pilot study.
Guillermo Delgado-García et al. Epilepsia 2023

Method for Classifying Schizophrenia Patients Based on Machine Learning.
Carmen Soria et al. J Clin Med 2023 12(13)

Development and economic assessment of machine learning models to predict glycosylated hemoglobin in type 2 diabetes.
Yi-Tong Tong et al. Front Pharmacol 2023 141216182

Revolutionizing Spinal Care: Current Applications and Future Directions of Artificial Intelligence and Machine Learning.
Mitsuru Yagi et al. J Clin Med 2023 12(13)

Generalizability of Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs Using an Adaptation of the Modified-2 Algorithm-Based Qualitative Criteria.
Qifei Dong et al. Acad Radiol 2023

An Enhanced Ensemble Deep Neural Network Approach for Elderly Fall Detection System Based on Wearable Sensors.
Zabir Mohammad et al. Sensors (Basel) 2023 23(10)

Single retinal image for diabetic retinopathy screening: performance of a handheld device with embedded artificial intelligence.
Fernando Marcondes Penha et al. Int J Retina Vitreous 2023 9(1) 41

AD-BERT: Using Pre-trained Language Model to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease.
Chengsheng Mao et al. J Biomed Inform 2023 104442

Machine learning-based intradialytic hypotension prediction of patients undergoing hemodialysis: A multicenter retrospective study.
Jingjing Dong et al. Comput Methods Programs Biomed 2023 240107698

Review of Visualization Approaches in Deep Learning Models of Glaucoma.
Byoungyoung Gu et al. Asia Pac J Ophthalmol (Phila) 2023

HomeADScreen: Developing Alzheimer's disease and related dementia risk identification model in home healthcare.
Maryam Zolnoori et al. Int J Med Inform 2023 177105146

The Influence of Using Novel Predictive Technologies on Judgments of Stigma, Empathy, and Compassion among Healthcare Professionals.
Daniel Z Buchman et al. AJOB Neurosci 2023 1-14

Using Artificial Intelligence to Diagnose Osteoporotic Vertebral Fractures on Plain Radiographs.
Li Shen et al. J Bone Miner Res 2023

Application of satellite remote sensing data and random forest approach to estimate ground-level PM concentration in Northern region of Thailand.
Pimchanok Wongnakae et al. Environ Sci Pollut Res Int 2023

Sensor-level MEG combined with machine learning yields robust classification of mild traumatic brain injury patients.
Juho Aaltonen et al. Clin Neurophysiol 2023 15379-87

Digital Biobanking and Big Data as a New Research Tool: A Position Paper.
Pamela Tozzo et al. Healthcare (Basel) 2023 11(13)

Implementing a Machine Learning Screening Tool for Malnutrition: Insights From Qualitative Research Applicable to Other Machine Learning-Based Clinical Decision Support Systems.
Melanie Besculides et al. JMIR Form Res 2023 7e42262

Curriculum frameworks and educational programs in artificial intelligence for medical students, residents, and practicing physicians: a scoping review protocol.
Raymond Tolentino et al. JBI Evid Synth 2023 21(7) 1477-1484

Data Science as a Core Competency in Undergraduate Medical Education in the Age of Artificial Intelligence in Health Care.
Puneet Seth et al. JMIR Med Educ 2023 9e46344

New recommendations of the International Committee of Medical Journal Editors: use of artificial intelligence.
Fernando Alfonso et al. Eur Heart J 2023

The Role of Artificial Intelligence Model Documentation in Translational Science: Scoping Review.
Tracey A Brereton et al. Interact J Med Res 2023 12e45903

ChatGPT and the Future of Digital Health: A Study on Healthcare Workers' Perceptions and Expectations.
Mohamad-Hani Temsah et al. Healthcare (Basel) 2023 11(13)

Artificial intelligence for predicting acute appendicitis: a systematic review.
Antoinette Lam et al. ANZ J Surg 2023

Editorial: Recent advances in artificial intelligence-empowered ultrasound tissue characterization for disease diagnosis, intervention guidance, and therapy monitoring.
Zhuhuang Zhou et al. Front Physiol 2023 141234611

Successes and challenges of artificial intelligence in cardiology.
Bert Vandenberk et al. Front Digit Health 2023 51201392

Using random forest machine learning on data from a large, representative cohort of the general population improves clinical spirometry references.
Kris Kristensen et al. Clin Respir J 2023

A Systematic Review and Meta-Analysis of Applying Deep Learning in the Prediction of the Risk of Cardiovascular Diseases From Retinal Images.
Wenyi Hu et al. Transl Vis Sci Technol 2023 12(7) 14

Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices.
Akshay Khunte et al. NPJ Digit Med 2023 6(1) 124

Towards Advanced Diagnosis and Management of Inherited Arrhythmia Syndromes: Harnessing the Capabilities of Artificial Intelligence and Machine Learning.
Babken Asatryan et al. Heart Rhythm 2023

Prediction of oxygen supplementation by a deep-learning model integrating clinical parameters and chest CT images in COVID-19.
Naoko Kawata et al. Jpn J Radiol 2023

Diagnostic accuracy of three computer-aided detection systems for detecting pulmonary tuberculosis on chest radiography when used for screening: Analysis of an international, multicenter migrants screening study.
Sifrash Meseret Gelaw et al. PLOS Glob Public Health 2023 3(7) e0000402