AI Medical Compendium Journal:
JMIR formative research

Showing 31 to 40 of 71 articles

Developing an ICD-10 Coding Assistant: Pilot Study Using RoBERTa and GPT-4 for Term Extraction and Description-Based Code Selection.

JMIR formative research
BACKGROUND: The International Classification of Diseases (ICD), developed by the World Health Organization, standardizes health condition coding to support health care policy, research, and billing, but artificial intelligence automation, while promi...

Understanding Providers' Attitude Toward AI in India's Informal Health Care Sector: Survey Study.

JMIR formative research
BACKGROUND: Tuberculosis (TB) is a major global health concern, causing 1.5 million deaths in 2020. Diagnostic tests for TB are often inaccurate, expensive, and inaccessible, making chest x-rays augmented with artificial intelligence (AI) a promising...

Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists' Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study.

JMIR formative research
BACKGROUND: The COVID-19 pandemic has significantly strained health care systems globally, leading to an overwhelming influx of patients and exacerbating resource limitations. Concurrently, an "infodemic" of misinformation, particularly prevalent in ...

Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network-Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey.

JMIR formative research
BACKGROUND: Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from ...

Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach.

JMIR formative research
BACKGROUND: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports o...

Evaluating Older Adults' Engagement and Usability With AI-Driven Interventions: Randomized Pilot Study.

JMIR formative research
BACKGROUND: Technologies that serve as assistants are growing more popular for entertainment and aiding in daily tasks. Artificial intelligence (AI) in these technologies could also be helpful to deliver interventions that assist older adults with sy...

Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study.

JMIR formative research
BACKGROUND: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions ...

AI Machine Learning-Based Diabetes Prediction in Older Adults in South Korea: Cross-Sectional Analysis.

JMIR formative research
BACKGROUND: Diabetes is prevalent in older adults, and machine learning algorithms could help predict diabetes in this population.

Psychological and Behavioral Insights From Social Media Users: Natural Language Processing-Based Quantitative Study on Mental Well-Being.

JMIR formative research
BACKGROUND: Depression significantly impacts an individual's thoughts, emotions, behaviors, and moods; this prevalent mental health condition affects millions globally. Traditional approaches to detecting and treating depression rely on questionnaire...

Developing a Machine Learning-Based Automated Patient Engagement Estimator for Telehealth: Algorithm Development and Validation Study.

JMIR formative research
BACKGROUND: Patient engagement is a critical but challenging public health priority in behavioral health care. During telehealth sessions, health care providers need to rely predominantly on verbal strategies rather than typical nonverbal cues to eff...