Surveys

Ovarian cancer recurrence prediction: comparing confirmatory to real world predictors with machine learning

Ovarian cancer is one of the deadliest cancers in women, with a 5-year survival rate of 17-28% in advanced stage (FIGO IIB-IV) disease and is often diagnosed at advanced stage. Machine learning (ML) has the potential to provide a better survival prognosis than traditional tools, and to shed further light on predictive factors. This study focuses on advanced stage ovarian cancer and contrasts exper...

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 engagement, and information dissemination. Powerful generative AI (GAI) tools like ChatGPT and other similar chatbots have emerged, facilitating user interactions with virtual conversational agents. However, the increasing use of GAI tools in medical resea...

Is Multimodal Better? A Systematic Review of Multimodal versus Unimodal Machine Learning in Clinical Decision-Making

Machine learning has demonstrated success in clinical decision-making, yet the added value of multimodal approaches over unimodal models remains uncle...

Socio-Demographic Modifiers Shape Large Language Models’ Ethical Decisions

Large language models’ (LLMs) alignment with ethical standards is unclear. We tested whether LLMs shift medical ethical decisions when given socio-dem...

Evaluating the Reliability of a Custom GPT in Full-Text Screening of a Systematic Review

Systematic reviewing is a time-consuming process that can be aided by artificial intelligence (AI). There are several AI options to assist with title/...

Evaluation synthesis analysis can be accelerated through text mining, searching, and highlighting: A case-study on data extraction from 631 UNICEF evaluation reports

UNICEF works to protect children’s rights and improve their well-being by partnering with governments and communities through various programs. These ...

Analyzing the Capacity of ChatGPT and Google to Provide Medical Information: Insights from Umbilical Cord Clamping

The optimal timing of umbilical cord clamping in neonatal care has been a subject of debate for decades. Recently, artificial intelligence (AI) has em...

AI-Driven and Automated Continuous Oxygen Saturation Monitoring and LTOT: A Systematic Review

Long-term oxygen therapy (LTOT) is essential for patients with chronic hypoxemia, particularly due to chronic obstructive pulmonary disease (COPD). Ho...

Bridging AI and Healthcare: A Scoping Review of Retrieval-Augmented Generation—Ethics, Bias, Transparency, Improvements, and Applications

Retrieval-augmented generation (RAG) is an emerging artificial intelligence (AI) strategy that integrates encoded model knowledge with external data s...

Causal Forests versus Inverse Probability of Treatment Weighting to adjust for Cluster-Level Confounding: A Parametric and Plasmode Simulation Study based on US Hosptial Electronic Health Record Data

Rapid innovation and new regulations increase the need for post-marketing surveillance of implantable devices. However, complex multi-level confoundin...

The I-KAPCAM-AI-Q: A Novel Instrument for Evaluating Health Care Providers’ AI Awareness in Italy

Background: Understanding healthcare providers’ readiness and attitudes is crucial for integrating AI in healthcare, yet no validated tool exists to e...

Real-world Validation of MedSearch: a conversational agent for real-time, evidence-based medical question-answering

Application of Large Language Models (LLMs) powered Conversation Agents (CAs) in healthcare has been evaluated using medical question-answering (QA) d...

Attitudes and Perceptions of Biomedical Journal Editors-in-Chief Towards the Use of Artificial Intelligence Chatbots in the Scholarly Publishing Process: A Cross-Sectional Survey

Artificial intelligence chatbots (AICs) are designed to mimic human conversations through text or speech, offering both opportunities and challenges i...

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...

Key predictors of maternal mild depression and anxiety in low resource settings: A machine learning approach

Maternal mental health (MMH) disorders, particularly depression and anxiety, are major public health concerns in low- and middle-income countries (LMI...

Large-scale Local Deployment of DeepSeek-R1 in Pilot Hospitals in China: A Nationwide Cross-sectional Survey

The open-source release of DeepSeek-R1, a high-performing large language model (LLM), enables local deployment in Chinese hospitals. However, empirica...

LLM-Based Web Data Collection for Research Dataset Creation

Researchers across many fields rely on web data to gain new insights and validate methods. However, assembling accurate and comprehensive datasets typ...

Status and Opportunities of Machine Learning Applications in Obstructive Sleep Apnea: A Narrative Review

Obstructive sleep apnea (OSA) is a prevalent and potentially severe sleep disorder characterized by repeated interruptions in breathing during sleep. ...

Short-term and long-term outcome prediction for patients with coronary artery disease using machine learning and comprehensive multi-center patient data

Revascularization decision-making for patients with coronary artery disease (CAD) can benefit from accurate patient outcome prediction. While previous...

Validation of an instrumented shoe insole framework for analyzing spatiotemporal gait metrics in healthy and neurodegenerative populations

Many neurological conditions negatively affect a person’s walking quality, which is a vital aspect of their quality of life. Gait quality, through the...