AIMC Topic: Male

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Distinguishing Rectal Cancer from Colon Cancer Based on the Support Vector Machine Method and RNA-sequencing Data.

Current medical science
Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Several studies have indicated that rectal cancer is significantly different from colon cancer in terms of treatment, prognosis, and metastasis. Recently, the differential...

Machine learning algorithm for characterizing risks of hypertension, at an early stage in Bangladesh.

Diabetes & metabolic syndrome
BACKGROUND AND AIMS: Hypertension has become a major public health issue as the prevalence and risk of premature death and disability among adults due to hypertension has increased globally. The main objective is to characterize the risk factors of h...

Sex-Specific Classification of Drug-Induced Torsade de Pointes Susceptibility Using Cardiac Simulations and Machine Learning.

Clinical pharmacology and therapeutics
Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a toxic side effect of many drugs. To assess TdP risk, safety regulatory guidelines require quantification of hERG channel block in vitro and QT interval prolongation in vivo for ...

A Machine Learning Approach to First Pass Reperfusion in Mechanical Thrombectomy: Prediction and Feature Analysis.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: Novel machine learning (ML) methods are being investigated across medicine for their predictive capabilities while boasting increased adaptability and generalizability. In our study, we compare logistic regression with machine learning ...

Machine learning analysis to predict the need for ankle foot orthosis in patients with stroke.

Scientific reports
We investigated the potential of machine learning techniques, at an early stage after stroke, to predict the need for ankle-foot orthosis (AFO) in stroke patients. We retrospectively recruited 474 consecutive stroke patients. The need for AFO during ...

Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The number of deaths from COVID-19 continues to surge worldwide. In particular, if a patient's condition is sufficiently severe to require invasive ventilation, it is more likely to lead to death than to recovery.

Reducing the Risk of Postoperative Complications After Robot-assisted Radical Prostatectomy in Prostate Cancer Patients: Results of an Audit and Feedback Intervention Following the Implementation of Prospective Data Collection.

European urology focus
BACKGROUND: Prospective data collection for perioperative outcomes might increase awareness of surgical results obtained for patients with prostate cancer (PCa) undergoing robot-assisted radical prostatectomy (RARP). This would prompt the implementat...

Deep-learning-based image reconstruction in dynamic contrast-enhanced abdominal CT: image quality and lesion detection among reconstruction strength levels.

Clinical radiology
AIM: To evaluate the use of deep-learning-based image reconstruction (DLIR) algorithms in dynamic contrast-enhanced computed tomography (CT) of the abdomen, and to compare the image quality and lesion conspicuity among the reconstruction strength lev...

A unified framework for personalized regions selection and functional relation modeling for early MCI identification.

NeuroImage
Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely adopted to investigate functional abnormalities in brain diseases. Rs-fMRI data is unsupervised in nature because the psychological and neurological labels are coarse-grain...

Alberta Stroke Program Early CT Score Calculation Using the Deep Learning-Based Brain Hemisphere Comparison Algorithm.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is a promising tool for the evaluation of stroke expansion to determine suitability for reperfusion therapy. The aim of this study was to validate deep learning-based AS...