Hospital-Based Medicine

Can artificial intelligence lower the global sudden cardiac death rate? A narrative review.

PURPOSE OF REVIEW: WHO defines SCD as sudden unexpected death either within 1 h of symptom onset (witnessed) or within 24 h of having been observed alive and symptom-free (unwitnessed). Sudden cardiac arrest is a major cause of mortality worldwide, with survival to hospital discharge for hospital cardiac arrest and in-hospital cardiac arrest being only 9.3 % and 21.2 %, respectively, despite treat...

Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.

Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent a growing global concern. Early detection of these conditions is crucial for timely intervention and prevention of adverse outcomes. In this study, we present Guardian-BERT (Guardian-Bidirectional Encoder Representations from Transformers), a novel approach for the early detection of NSSI and suicid...

Developing a rapid screening tool for high-risk ICU patients of sepsis: integrating electronic medical records with machine learning methods for mortality prediction in hospitalized patients-model establishment, internal and external validation, and visualization.

OBJECTIVES: To develop a machine learning-based prediction model using clinical data from the first 24 h of ICU admission to enable rapid screening an...

Classifying Unstructured Text in Electronic Health Records for Mental Health Prediction Models: Large Language Model Evaluation Study.

BACKGROUND: Prediction models have demonstrated a range of applications across medicine, including using electronic health record (EHR) data to identi...

Use of artificial intelligence to study the hospitalization of women undergoing caesarean section.

OBJECTIVE: The incidence of caesarean sections (CSs) has increased significantly in recent years, especially in developed countries. This study aimed ...

Task-oriented robotic rehabilitation for back mobility and functioning in a post-intensive care unit obese patient: A case report.

BackgroundIntensive care unit (ICU) acquired weakness is a detrimental condition characterized by muscle weakness, difficulty in weaning from mechanic...

Evaluating ChatGPT-4o as a decision support tool in multidisciplinary sarcoma tumor boards: heterogeneous performance across various specialties.

BACKGROUND AND OBJECTIVES: Since the launch of ChatGPT in 2023, large language models have attracted substantial interest to be deployed in the health...

Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence-Assisted Cancer Diagnosis.

The potential of artificial intelligence (AI) in digital pathology is limited by technical inconsistencies in the production of whole slide images (WS...

Using Inertial Measurement Units and Machine Learning to Classify Body Positions of Adults in a Hospital Bed.

In hospitals, timely interventions can prevent avoidable clinical deterioration. Early recognition of deterioration is vital to stopping further decli...

Decoding the blueprint of receptor binding by filoviruses through large-scale binding assays and machine learning.

Evidence suggests that bats are important hosts of filoviruses, yet the specific species involved remain largely unidentified. Niemann-Pick C1 (NPC1) ...

Machine learning validation of a simple prediction model for the correlation between advanced age and clinical outcomes in patients with aneurysmal subarachnoid hemorrhage.

Adverse effects of advanced age and poor initial neurological status on outcomes of patients with aneurysmal subarachnoid hemorrhage (SAH) have been d...

The Role of Artificial Intelligence in Health Care.

Artificial intelligence (AI) plays a leading role in transmuting the field of healthcare. Numerous aspects of AI have been incorporated into the healt...

Predicting admission for fall-related injuries in older adults using artificial intelligence: A proof-of-concept study.

AIM: Pre-injury frailty has been investigated as a tool to predict outcomes of older trauma patients. Using artificial intelligence principles of mach...

Service robots in caring for older adults: Uncovering the current conceptual and intellectual structures and future research agenda.

Service robots have supported human activity, mainly caring for older adults, for many years. However, a new generation of service robots empowered by...

Developing a decision support tool to predict delayed discharge from hospitals using machine learning.

BACKGROUND: The growing demand for healthcare services challenges patient flow management in health systems. Alternative Level of Care (ALC) patients ...

Machine learning assessment of dredging impacts on the phytoplankton community on the Brazilian equatorial margin: A multivariate analysis.

Dredging in estuarine systems significantly impacts phytoplankton communities, with suspended particulate matter (SPM) and dissolved aluminum (Al) ser...

Multimodal deep learning for predicting in-hospital mortality in heart failure patients using longitudinal chest X-rays and electronic health records.

Amid an aging global population, heart failure has become a leading cause of hospitalization among older people. Its high prevalence and mortality rat...

Novel silver nanoparticle-based biomaterials for combating biofilms.

BACKGROUND: is a significant nosocomial pathogen that has developed resistance to multiple antibiotics, often forming biofilms that enhance its virul...

Predicting 28-day all-cause mortality in patients admitted to intensive care units with pre-existing chronic heart failure using the stress hyperglycemia ratio: a machine learning-driven retrospective cohort analysis.

Chronic heart failure (CHF) poses a significant threat to human health. The stress hyperglycemia ratio (SHR) is a novel metric for accurately assessin...

Prediction of mortality in intensive care unit with short-term heart rate variability: Machine learning-based analysis of the MIMIC-III database.

BACKGROUND: Prognosis prediction in the intensive care unit (ICU) traditionally relied on physiological scoring systems based on clinical indicators a...