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Construction of prediction model of early glottic cancer based on machine learning.

Acta oto-laryngologica
BACKGROUND: The early diagnosis of glottic laryngeal cancer is the key to successful treatment, and machine learning (ML) combined with narrow-band imaging (NBI) laryngoscopy provides a new idea for the early diagnosis of glottic laryngeal cancer.

Allied Health Professionals' Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey.

JMIR formative research
BACKGROUND: Artificial intelligence (AI) has the potential to address growing logistical and economic pressures on the health care system by reducing risk, increasing productivity, and improving patient safety; however, implementing digital health te...

Advanced Technology in a Real-World Rehabilitation Setting: Longitudinal Observational Study on Clinician Adoption and Implementation.

Journal of medical Internet research
BACKGROUND: Advanced technologies are becoming increasingly accessible in rehabilitation. Current research suggests technology can increase therapy dosage, provide multisensory feedback, and reduce manual handling for clinicians. While more high-qual...

Research on multi-label recognition of tongue features in stroke patients based on deep learning.

Scientific reports
Stroke has become the leading cause of disability in adults worldwide. Early precise rehabilitation intervention is crucial for the recovery of stroke patients, with the key lying in accurately identifying patients' physical characteristics during th...

Development of risk models for early detection and prediction of chronic kidney disease in clinical settings.

Scientific reports
Chronic kidney disease (CKD) imposes a high burden with high mortality and morbidity rates. Early detection of CKD is imperative in preventing the adverse outcomes attributed to the later stages. Therefore, this study aims to utilize machine learning...

Machine learning algorithms in constructing prediction models for assisted reproductive technology (ART) related live birth outcomes.

Scientific reports
Currently applicable models for predicting live birth outcomes in patients who received assisted reproductive technology (ART) have methodological or study design limitations that greatly obstruct their dissemination and application. Models suitable ...

Development and validation of a web-based calculator for determining the risk of psychological distress based on machine learning algorithms: A cross-sectional study of 342 lung cancer patients.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: Early and accurate identification of the risk of psychological distress allows for timely intervention and improved prognosis. Current methods for predicting psychological distress among lung cancer patients using readily available data are ...

Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT.

Scientific reports
Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-small cell lung cancer (NSCLC) tumours holds significant management implications. We assessed the performance of radiomics-based models in distinguishing ...

A deep learning-based ADRPPA algorithm for the prediction of diabetic retinopathy progression.

Scientific reports
As an alternative to assessments performed by human experts, artificial intelligence (AI) is currently being used for screening fundus images and monitoring diabetic retinopathy (DR). Although AI models can provide quasi-clinician diagnoses, they rar...

A machine learning-based clinical predictive tool to identify patients at high risk of medication errors.

Scientific reports
A medication error is an inadvertent failure in the drug therapy process that can cause serious harm to patients by increasing morbidity and mortality and are associated with significant economic costs to the healthcare system. Medication reconciliat...