Hospital-Based Medicine

Use of Machine Learning to Predict Hospital Admission for EMS-Treated Infants After a Suspected BRUE.

OBJECTIVES: This study explored the use of different applied machine learning (ML) classification algorithms to predict hospital admission for infants treated by emergency medical services (EMS) after a suspected brief resolved unexplained event (BRUE). METHODS: Data from a large regionalized pediatric care system were obtained for infants in which paramedic suspected a BRUE and who were transport...

Precision imaging and evolving therapies in paragangliomas and pheochromocytomas: from molecular diagnostics to imaging-guided management.

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from neural crest-derived chromaffin tissue, marked by clinical heterogeneity and substantial genetic underpinnings. With up to 70% of cases linked to germline or somatic mutations, including Succinate DeHydrogenase genetic alterations (SDHx), and Von Hippel-Lindau (VHL), genetic profiling is central to diagnos...

Early Prediction of Adverse Stroke Outcomes using Non-clinical Factors and Missing Data: A Machine Learning Study.

Introduction Early prediction of stroke outcomes using prognostic tools may help clinical decision making and inform resource allocation. However, cli...

Personalized Diabetes Treatment Support Using Large Language Models Fine-Tuned on Electronic Health Records: Development and Evaluation Study.

BACKGROUND: Effective diabetes management requires individualized treatment strategies tailored to patients' clinical characteristics. With recent adv...

Enhancing readability and understandability of vascular surgery discharge summaries using artificial intelligence.

ObjectivesThis study aimed to assess whether Large Language Models (LLMs), like ChatGPT-4, could simplify discharge summaries for vascular surgery pat...

Advanced deep learning strategies in nanopore RNA sequencing.

The epitranscriptome comprises chemical modifications found on RNA molecules that play essential roles in co- and post-transcriptional gene regulation...

Plasma metabolomic signatures in patients with multidrug-resistant bacterial sepsis.

BACKGROUND AND OBJECTIVE: Multidrug-resistant (MDR) bacterial infections are a leading cause of sepsis-related death. A rapid method to identify patie...

Dental students' knowledge, perceptions, and educational needs regarding artificial intelligence: a multinational cross-sectional survey.

AIMS: To explore undergraduate dental students' AI knowledge, perceptions, and concerns, and to identify their educational needs based on these findin...

Advances in the postoperative care of the liver transplant recipient.

PURPOSE OF REVIEW: Survival rates following liver transplantation now exceed 90% at one year. However, the patient group undergoing liver transplantat...

Early individualized risk prediction using clinical data for children during the febrile phase of dengue in outpatient settings in Vietnam and Thailand.

Dengue severity prediction models are usually developed using hospitalized patient data, but triage and hospital admission are mainly evaluated in out...

[Application of molecularly imprinted polymers-based sensors for determination of acute coronary syndrome biomarkers].

Cardiovascular diseases （CVDs） are among the leading cause of global morbidity and mortality. Due to their high prevalence and often asymptomatic prog...

Utilising unsupervised machine learning to predict outbreaks of respiratory tract infections in acute Irish hospitals (2016-2021).

OBJECTIVES: To apply unsupervised machine learning (ML) to predict outbreaks of respiratory tract infections (RTIs) in acute Irish hospitals (2016-202...

Development and internal validation of machine learning in predicting prognosis of acute kidney injury patients in resource-limited setting.

BACKGROUND: Machine learning models for predicting acute kidney injury (AKI) prognosis have primarily been developed in resource-rich settings, with l...

Current perspectives in cardiogenic shock.

Cardiogenic shock (CS) remains a leading cause of death in intensive cardiac care. Outcomes are limited by delayed recognition of hypoperfusion, heter...

Predicting recurrent cardiac arrest within one year after surviving In-Hospital Cardiac Arrest using a machine learning model.

BACKGROUND: Patients discharged alive after in-hospital cardiac arrest (IHCA) have an increased mortality up to a year after hospital discharge. Impro...

Multidisciplinary Team Diagnosis and Treatment of well-differentiated thyroid carcinoma: Current Landscape and Future Prospects.

BACKGROUND: The incidence of thyroid cancer has increased markedly in recent years, largely driven by well-differentiated thyroid carcinoma (WDTC). WD...

Maximizing impact of explainable artificial intelligence in radiotherapy: a critical review.

Objective.Artificial intelligence (AI) can enable automation, improve treatment accuracy, allow for a more efficient workflow, and improve the cost-ef...

Expert Consensus on the Artificial Intelligence Proficiency Competency List and Assessment Framework for Medical Students (2025 Edition).

To cultivate composite medical professionals capable of adapting to the development of intelligent healthcare,this consensus is grounded in the compet...

Seasonal variation in BMI outcomes at 6 months: secondary analyses of a multidisciplinary healthy lifestyle programme for children and adolescents with obesity.

BACKGROUND: While international evidence suggests seasonal variations may influence outcomes of interventions for pediatric obesity, data for Aotearoa...

Advancing Psychiatric Safety With the Predictive Risk Identification for Mental Health Events Tool: Retrospective Cohort Study.

BACKGROUND: Patient safety incidents are a leading cause of harm in psychiatric settings, yet early warning systems (EWS) tailored to mental health re...