Hospital-Based Medicine

Interpretable Machine Learning for Stroke Recovery: Predicting Discharge and 3-Month Functional Outcomes.

IntroductionStroke is a leading cause of disability worldwide. This study uses Machine Learning models to investigate factors influencing modified Rankin Scale scores at discharge and three months post-discharge.MethodsData from 116 stroke patients were analyzed using four predictive models: Logistic Regression, Support Vector Machine, Random Forest, and Extreme Gradient Boosting (XGB). Shapley Ad...

Deep learning-based battery health prediction for enhancing electric vehicle performance.

Reliable and sustainable battery diagnostics are essential for advancing electric vehicle (EV) technologies and fulfilling Sustainable Development Goal 7 (SDG 7): Affordable and Clean Energy. This study proposes a hybrid deep learning framework that integrates one-dimensional Convolutional Neural Networks (1D-CNNs), Temporal Convolutional Networks (TCNs), and Long Short-Term Memory (LSTM) layers, ...

Artificial intelligence in head and neck cancer rehabilitation services: current state and future perspectives.

PURPOSE OF REVIEW: This review evaluates the current state of artificial intelligence (AI) in head and neck cancer (HNC) rehabilitation services by ma...

Scaling genomic reanalysis to unlock diagnoses and transform rare disease care.

Genomic reanalysis can identify causative variants for rare diseases as patient phenotypes evolve and gene-disease knowledge expands. Despite its diag...

Artificial Intelligence in African Cardiovascular Care: Opportunities, Challenges, and Pathways to Improved Outcomes.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality in Africa, accounting for over 1 million deaths annually. As CVD preva...

Implantable CB/PVDF/TPU Sensors for In Situ Monitoring of Internal Temperature Changes in Lithium-Ion Batteries.

In situ monitoring of lithium-ion battery thermal runaway is limited by the invasiveness and insufficient sensitivity of conventional thermometry. The...

Developing a Service Quality Index System for AI Health Care Chatbots: Mixed Methods Study.

BACKGROUND: Artificial intelligence (AI) health care chatbots are gaining widespread adoption worldwide. It is imperative to understand the service qu...

Interpretable machine learning and deep neural networks for ICU admission prediction in paediatric respiratory patients.

Conversational AI for remote monitoring in heart failure: a prospective controlled pilot study.

AIMS: Heart failure (HF) requires scalable strategies to detect decompensation early and reduce hospitalizations. Existing telemonitoring tools are of...

Prediction of Major Stroke (NIHSS > 5) Based on MR Perfusion Imaging Using a 3D ResNet.

PURPOSE: Prediction of stroke symptoms from perfusion patterns in ischemic stroke imaging would be desirable for decision making in relevant clinical ...

Prediction of 9 Artificial Intelligence-based Intraocular Lens Power Calculation Formulas in Long Caucasian Eyes.

PURPOSE: To compare accuracy of nine artificial intelligence (AI)- based intraocular lens (IOL) power calculation formulas in eyes with axial length >...

Development and validation of predictive models for prognostic assessment in patients with acute non-ST-segment elevation myocardial infarction: a multicentre real-world study from China.

BACKGROUND: Few models specifically predict the prognoses of non-ST-segment elevation myocardial infarction (NSTEMI) patients. Additionally, these mod...

Large Language Model for Postoperative Clinical Decision Support in a Neurosurgery Ward in the Gambia: A Prospective Pilot Feasibility Study.

BACKGROUND AND OBJECTIVES: Access to specialty surgical care is growing in many low-income countries, but it remains unclear how hospital workforces c...

A deep learning model integrating structured data and clinical text for predicting atrial fibrillation recurrence.

Multimodal perioperative data from patients undergoing atrial fibrillation (AF) ablation offer valuable insights for stratifying recurrence risk, yet ...

Small-bowel capsule endoscopy - from clinic to couch: time to go green?

PURPOSE OF REVIEW: Small-bowel capsule endoscopy (SBCE) has transformed small-intestine diagnostics by enabling direct, noninvasive mucosal visualizat...

Artificial intelligence to support ultrasound in the detection of developmental dysplasia of the hip : a scoping review.

AIMS: Ultrasound is a highly sensitive method to detect developmental dysplasia of the hip (DDH). However, the cost of expert sonographers performing ...

Toward an explainable AI-Based clinical decision support system for predicting adverse outcomes in Rhabdomyolysis.

Rhabdomyolysis is a severe condition with high morbidity and mortality, driven by complications like acute kidney injury. Early risk stratification re...

Association between monocyte-to-lymphocyte ratio and mortality in patients with acute pancreatitis requiring intensive care unit admission: a retrospective cohort study and predictive model establishment based on machine learning.

The purpose of this study was to evaluate the predictive value of monocyte-to-lymphocyte ratio (MLR) on the short-term (28 days) and long-term (365 da...

CLAIRE: a unified framework for reporting and assessing artificial intelligence in diagnostic imaging.

Artificial intelligence (AI) models for diagnostic imaging face reproducibility challenges due to inconsistent reporting. Existing guidelines also lac...

Evolving strategies in prostate cancer: Emerging approaches and unmet needs from the Bridging the Gaps in Prostate Cancer expert panel.

BACKGROUND: The expansion of treatment options for prostate cancer (PC) has improved disease-specific and overall survival outcomes but has also raise...