Hospital-Based Medicine

Surveillance

Latest AI and machine learning research in surveillance for healthcare professionals.

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Detection of patient metadata in published articles for genomic epidemiology using machine learning and large language models

Patient metadata exist in published articles, but are often dis-connected from genome sequences in databases, limiting their utility for genomic epidemiology. The objective of this study was to develop and evaluate natural language processing methods to facilitate the large-scale detection of patient metadata associated with reports of genome sequencing in published articles, drawing on the case o...

The use of Artificial Intelligence in the out of hospital care settings: A Scoping Review

Out of hospital services face significant challenges, including growing patient demand, workforce limitations, and evolving care pathways. Artificial Intelligence (AI) technologies offer potential solutions, but their application in out-of-hospital settings remains inconsistently implemented and poorly understood. To identify the types of AI technologies being applied in out-of-hospital settings, ...

TOWARDS AN AI-DRIVEN REGISTRY FOR POSTOPERATIVE COMPLICATIONS: A PROOF-OF-CONCEPT STUDY EVALUATING THE OPPORTUNITIES AND CHALLENGES OF AI-MODELS

Continuous quality improvement is essential in surgery, with clinical registries and quality improvement programs (QIPs) playing a key role. Postopera...

Validation of Natural Language Processing for Surgical Complication Surveillance: Detecting Eleven Postoperative Complications from Electronic Health Records

Postoperative complications (PCs) rates are crucial quality metrics in surgery, as they reflect both patient outcomes, perioperative care effectivenes...

Automated Extraction of Mortality Information from Publicly Available Sources Using Language Models

Mortality is a critical variable in healthcare research, especially for evaluating medical product safety and effectiveness. However, inconsistencies ...

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...

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...

Clinicodemographic Prediction of Overall Survival in Patients with Head and Neck Merkel Cell Carcinoma: A Machine Learning Approach

Merkel cell carcinoma (MCC) is a rare cutaneous neuroendocrine malignancy with a higher case-fatality rate than melanoma. The prognosis of MCC is comp...

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...

Fast and Trustworthy Nowcasting of Dengue Fever: A Case Study Using Attention-Based Probabilistic Neural Networks in São Paulo, Brazil

Nowcasting methods are crucial in infectious disease surveillance, as reporting delays often lead to underestimation of recent incidence and can impai...

AI-Driven Pharmacovigilance and Molecular Profiling of Fluoroquinolone-Associated Cardiotoxicity in the UAE: A Geospatial and Machine Learning Analysis with Structural Modification Strategies (2018-2023)

Fluoroquinolones, while clinically indispensable, carry underappreciated cardiovascular risks, particularly QT prolongation and life-threatening arrhy...

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...

AI-Enabled Diagnostic Prediction within Electronic Health Records to Enhance Biosurveillance and Early Outbreak Detection

Detecting infectious disease outbreaks promptly is crucial for effective public health responses, minimizing transmission, and enabling critical inter...

Mapping open educational resources on how to justify, design, conduct, analyse, and share randomised clinical trials: a landscape analysis

To map open educational resources on how to justify, design, conduct, analyse, and share randomised clinical trials of healthcare interventions. Lands...

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...

Data Resource Profile: Linking electronic health and social records to study and lower health inequalities in cardiovascular diseases (BIG-HEART)

The BIG-HEART cohort was established to study and reduce health inequalities in cardiovascular disease by linking rich, multidimensional electronic he...

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...

Evaluation of Large Language Models in Medical Examinations: A Scoping Review Protocol

Large language models (LLMs) demonstrate human-level performance in three key domains: linguistic understanding, knowledge-based reasoning, and comple...

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...

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