Hospital-Based Medicine

Predicting in-hospital mortality among patients admitted with a diagnosis of heart failure: a machine learning approach.

Existing risk prediction models for hospitalized heart failure patients are limited. We identified patients hospitalized with a diagnosis of heart failure between 7 May 2013 and 26 April 2022 from a large academic, quaternary care medical centre (training cohort). Demographics, medical comorbidities, vitals, and labs were collected and were used to construct random forest machine learning models t...

How artificial intelligence could transform emergency care.

Artificial intelligence (AI) in healthcare is the ability of a computer to perform tasks typically associated with clinical care (e.g. medical decision-making and documentation). AI will soon be integrated into an increasing number of healthcare applications, including elements of emergency department (ED) care. Here, we describe the basics of AI, various categories of its functions (including mac...

vEpiNet: A multimodal interictal epileptiform discharge detection method based on video and electroencephalogram data.

To enhance deep learning-based automated interictal epileptiform discharge (IED) detection, this study proposes a multimodal method, vEpiNet, that lev...

On the relationship between various anticoagulants and robot-assisted radical prostatectomy: a single-surgeon serial analysis.

Prostate cancer patients often have other health conditions and take anticoagulants. It was believed that surgery under anticoagulants could worsen su...

Machine learning for enhanced prognostication: predicting 30-day outcomes following posterior fossa decompression surgery for Chiari malformation type I in a pediatric cohort.

OBJECTIVE: Chiari malformation type I (CM-I) is a congenital disorder occurring in 0.1% of the population. In symptomatic cases, surgery with posterio...

Machine learning approach to assess the association between anthropometric, metabolic, and nutritional status and semen parameters.

Many lifestyle factors, such as nutritional imbalance leading to obesity, metabolic disorders, and nutritional deficiency, have been identified as pot...

Predictive modeling of deep vein thrombosis risk in hospitalized patients: A Q-learning enhanced feature selection model.

Deep vein thrombosis (DVT) represents a critical health concern due to its potential to lead to pulmonary embolism, a life-threatening complication. E...

Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission.

BACKGROUND AND OBJECTIVE: Critically ill children may suffer from impaired neurocognitive functions years after ICU (intensive care unit) discharge. T...

Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review.

Atrial fibrillation (AF) stands as the predominant arrhythmia observed in ICU patients. Nevertheless, the absence of a swift and precise method for pr...

Multimodal Machine Learning for Prediction of 30-Day Readmission Risk in Elderly Population.

BACKGROUND: Readmission within 30 days is a prevalent issue among elderly patients, linked to unfavorable health outcomes. Our objective was to develo...

Generative artificial intelligence in surgery.

Generative artificial intelligence is able to collect, extract, digest, and generate information in an understandable way for humans. As the first sur...

Predicting ischemic stroke patients' prognosis changes using machine learning in a nationwide stroke registry.

Accurately predicting the prognosis of ischemic stroke patients after discharge is crucial for physicians to plan for long-term health care. Although ...

Initial experience of a single surgeon for safety and feasibility of the Versius Robotic System in robot-assisted cholecystectomy and hernia repair.

This study aimed to evaluate the feasibility, safety, and perioperative outcomes of cholecystectomy and hernia repair performed with the Versius Robot...

Outcomes of robot-assisted radical prostatectomy in men after trans-urethral resection of the prostate: a matched-pair analysis.

Prior history of transurethral resection of the prostate (TURP) can complicate Robot-assisted radical prostatectomy (RARP). Very few studies analyse t...

An Artificial Intelligence-Supported Medicinal Chemistry Project: An Example for Incorporating Artificial Intelligence Within the Pharmacy Curriculum.

OBJECTIVE: This study aims to integrate and use AI to teach core concepts in a medicinal chemistry course and to increase the familiarity of pharmacy ...

Bioinspiration and biomimetics in marine robotics: a review on current applications and future trends.

Over the past few years, the research community has witnessed a burgeoning interest in biomimetics, particularly within the marine sector. The study o...

Is the robotic approach the future of distal pancreatectomy with splenectomy? A propensity score matched analysis.

Our study provides a comparative analysis of the Laparo-Endoscopic Single Site (LESS) and robotic surgical approaches for distal pancreatectomy and sp...

Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database.

Unplanned readmission after primary total knee arthroplasty (TKA) costs an average of US $39,000 per episode and negatively impacts patient outcomes. ...

Performance evaluation of deep learning based stream nitrate concentration prediction model to fill stream nitrate data gaps at low-frequency nitrate monitoring basins.

Accurate and frequent nitrate estimates can provide valuable information on the nitrate transport dynamics. The study aimed to develop a data-driven m...

Using Natural Language Processing to Identify Home Health Care Patients at Risk for Diagnosis of Alzheimer's Disease and Related Dementias.

This study aimed to: (1) validate a natural language processing (NLP) system developed for the home health care setting to identify signs and symptoms...