AIMC Topic:
Middle Aged

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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...

Prediction of prognosis in patients with cerebral contusions based on machine learning.

Scientific reports
Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effective...

Deep-learning-based extraction of circle of Willis topology with anatomical priors.

Scientific reports
The circle of Willis (CoW) is a circular arrangement of arteries in the human brain, exhibiting significant anatomical variability. The CoW is extensively studied in relation to neurovascular pathologies, with certain anatomical variants previously l...

Bidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.

Scientific reports
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence. The chances of treating the Recurrence of cervic...

Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma.

Scientific reports
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the...

Web application using machine learning to predict cardiovascular disease and hypertension in mine workers.

Scientific reports
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 201...

Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features.

Radiation oncology (London, England)
BACKGROUND AND PURPOSE: Timely identification of local failure after stereotactic radiotherapy for brain metastases allows for treatment modifications, potentially improving outcomes. While previous studies showed that adding radiomics or Deep Learni...

Food for thought: a qualitative assessment of medical trainee and faculty perceptions of nutrition education.

BMC medical education
BACKGROUND: The American Society of Clinical Nutrition recommends 37 to 44 h of undergraduate medical nutrition education. The Total Health Curriculum at Geisinger Commonwealth School of Medicine (GCSOM) contains 14 h of objective-based nutritional i...

A new risk assessment model of venous thromboembolism by considering fuzzy population.

BMC medical informatics and decision making
BACKGROUND: Inpatients with high risk of venous thromboembolism (VTE) usually face serious threats to their health and economic conditions. Many studies using machine learning (ML) models to predict VTE risk overlook the impact of class-imbalance pro...