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Machine learning-based 28-day mortality prediction model for elderly neurocritically Ill patients.

Computer methods and programs in biomedicine
BACKGROUND: The growing population of elderly neurocritically ill patients highlights the need for effective prognosis prediction tools. This study aims to develop and validate machine learning (ML) models for predicting 28-day mortality in intensive...

Classification of α-thalassemia data using machine learning models.

Computer methods and programs in biomedicine
BACKGROUND: Around 7% of the global population has congenital hemoglobin disorders, with over 300,000 new cases of α-thalassemia annually. Diagnosis is costly and inaccurate in low-income regions, often relying on complete blood count (CBC) tests. Th...

An EEG-based emotion recognition method by fusing multi-frequency-spatial features under multi-frequency bands.

Journal of neuroscience methods
BACKGROUND: Recognition of emotion changes is of great significance to a person's physical and mental health. At present, EEG-based emotion recognition methods are mainly focused on time or frequency domains, but rarely on spatial information. Theref...

Clinicians' perspectives on the use of artificial intelligence to triage MRI brain scans.

European journal of radiology
Artificial intelligence (AI) tools can triage radiology scans to streamline the patient pathway and also relieve clinician workload. Validated AI tools can mitigate the delays in reporting scans by flagging time-sensitive and actionable findings. In ...

Artificial intelligence-enhanced navigation for nerve recognition and surgical education in laparoscopic colorectal surgery.

Surgical endoscopy
BACKGROUND: Devices that help educate young doctors and enable safe, minimally invasive surgery are needed. Eureka is a surgical artificial intelligence (AI) system that can intraoperatively highlight loose connective tissues (LCTs) in the dissected ...

An accelerated deep learning model can accurately identify clinically important humeral and scapular landmarks on plain radiographs obtained before and after anatomic arthroplasty.

International orthopaedics
PURPOSE: Accurate identification of radiographic landmarks is fundamental to characterizing glenohumeral relationships before and sequentially after shoulder arthroplasty, but manual annotation of these radiographs is laborious. We report on the use ...

Differential Diagnosis of Urinary Cancers by Surface-Enhanced Raman Spectroscopy and Machine Learning.

Analytical chemistry
Bladder, kidney, and prostate cancers are prevalent urinary cancers, and developing efficient detection methods is of significance for the early diagnosis of them. However, noninvasive and sensitive detection of urinary cancers still challenges tradi...

Estimation of Forces and Powers in Ergometer and Scull Rowing Based on Long Short-Term Memory Neural Networks.

Sensors (Basel, Switzerland)
Analyzing performance in rowing, e.g., analyzing force and power output profiles produced either on ergometer or on boat, is a priority for trainers and athletes. The current state-of-the-art methodologies for rowing performance analysis involve the ...

Enhancing Medical Student Engagement Through Cinematic Clinical Narratives: Multimodal Generative AI-Based Mixed Methods Study.

JMIR medical education
BACKGROUND: Medical students often struggle to engage with and retain complex pharmacology topics during their preclinical education. Traditional teaching methods can lead to passive learning and poor long-term retention of critical concepts.

Real-Time Analytics and AI for Managing No-Show Appointments in Primary Health Care in the United Arab Emirates: Before-and-After Study.

JMIR formative research
BACKGROUND: Primary health care (PHC) services face operational challenges due to high patient volumes, leading to complex management needs. Patients access services through booked appointments and walk-in visits, with walk-in visits often facing lon...