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Identifying and Reporting Dependent Adult abuse

Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.

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Predicting mortality in critically ill patients with hypertension using machine learning and deep learning models

Accurate prediction of mortality in critically ill patients with hypertension admitted to the Intensive Care Unit (ICU) is essential for guiding clinical decision-making and improving patient outcomes. Traditional prognostic tools often fall short in capturing the complex interactions between clinical variables in this high-risk population. Recent advances in machine learning (ML) and deep learnin...

Finding the Clinical Traces of Cognitive Impairment in Patients with Heart Failure: A Natural Language Processing Study of Clinical Letters from Routine Care

Cognitive impairment is common in patients with heart failure, but to which extent cognitive complaints are evaluated and listed in clinical practice is unknown. Therefore, this study aims to identify whether cognitive complaints are listed in clinical notes of patients with heart failure, consistent with listed complaints in clinical notes of patients attending memory clinics, by using natural la...

Development of Interactive Nomograms for Predicting Short-Term Survival in ICU Patients with Aplastic Anemia

Aplastic anemia is a severe hematologic disorder marked by pancytopenia and bone marrow failure. ICU admission often reflects disease progression or c...

Towards automated fetal brain biometry reporting for 3-dimensional T2-weighted 0.55-3T magnetic resonance imaging at 20-40 weeks gestational age range

The detailed assessment of fetal brain maturation and development involves morphological evaluation, gyration analysis, and reliable biometric measure...

OphthUS-GPT: Multimodal AI for Automated Reporting in Ophthalmic B-Scan Ultrasound

The rapid advancement of AI in ophthalmology is transforming diagnostics, especially in resource-limited settings. The shortage of ophthalmologists an...

Protocol for developing the reporting guideline for the use of chatbots and other Generative Artificial intelligence tools in MEdical Research (GAMER)

The integration of artificial intelligence (AI) has revolutionized medical research, offering innovative solutions for data collection, patient engage...

Evaluating the Reporting Quality of 21,041 Randomized Controlled Trial Articles

Incomplete reporting of a study’s methods and results hinders efforts to evaluate and reproduce research findings in randomized controlled trials (RCT...

Large Language Models in Radiology Reporting—A Systematic Review of Performance, Limitations, and Clinical Implications

Large language models (LLMs) have emerged as potential tools for automated radiology reporting. However, concerns regarding their fidelity, reliabilit...

Current Limitations of Electronic Health Record Systems in Supporting Pragmatic Clinical Trials: Insights from the eMERGE Consortium

Pragmatic clinical trials (PCTs) evaluate interventions in real-world settings, often using electronic health records (EHRs) for efficient data collec...

Using Artificial Intelligence (AI) to Model Clinical Variant Reporting for Next Generation Sequencing (NGS) Oncology Assays

Targeted next generation sequencing (NGS) of somatic DNA is now routinely used for diagnostic and predictive reporting in the oncology clinic. The exp...

ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL METHODS FOR MODELLING AND FORECASTING INFLUENZA AND INFLUENZA-LIKE ILLNESS: A SCOPING REVIEW

The persistnt resurgence of influence and influenza-like illness despite concerted vaccination interventions is a global health burden, thus necessita...

Development and validation of diagnostic and prognostic prediction tools for dental caries in young children: A protocol

Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection, and impaired qualit...

Large Language Models for Supporting Clear Writing and Detecting Spin in Randomized Controlled Trials in Oncology

Accurate interpretation of randomized controlled trial (RCT) results is essential for guiding clinical practice in oncology. Reporting “spin” can misr...

AI Implementation in U.S. Healthcare and Its Association With Elder Mortality and Quality of Care

Hospitals are increasingly adopting artificial intelligence (AI) tools in clinical care. However, their overall impact on the health of older adults r...

Natural Language Processing Techniques to Detect Delirium in Hospitalized Patients from Clinical Notes: A Systematic Review

Delirium is a serious and common condition in hospitalized patients, associated with increased morbidity, mortality, and healthcare costs. Early detec...

Barriers and Facilitators to the Implementation of Artificial Intelligence Enabled Diabetes Interventions in Lower-Middle-Income Countries: A Systematic Review Protocol

Diabetes represents an emerging global health crisis, with lower-middle-income countries experiencing a fast growth in prevalence. Diabetes care in th...

Development of Machine Learning Algorithms Using EEG Data to Detect the Presence of Chronic Pain

Chronic pain impacts more than one in five adults in the United States (US) and the costs associated with the condition amount to hundreds of billions...

Automatic ICD coding using LLMs: a systematic review

Manual assignment of International Classification of Diseases (ICD) codes is error-prone. Transformer-based large language models (LLMs) have been pro...

Temperature-Driven Variability in Emergency Diagnostic Accuracy by a Leading Language Model

To determine the impact of the temperature parameter on GPT-4o’s diagnostic accuracy when evaluating emergency medicine cases and assess the effect on...

Artificial Intelligence for Surgical Scene Understanding: A Systematic Review and Reporting Quality Meta-Analysis

Surgical scene understanding (SSU) describes the use of Artificial Intelligence (AI) to provide an understanding of visual components of surgical imag...

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