AIMC Topic: Middle Aged

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Machine learning applied to near-infrared spectra for clinical pleural effusion classification.

Scientific reports
Lung cancer patients with malignant pleural effusions (MPE) have a particular poor prognosis. It is crucial to distinguish MPE from benign pleural effusion (BPE). The present study aims to develop a rapid, convenient and economical diagnostic method ...

Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Clinical and translational science
Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad-spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two-center ...

Multitask fMRI and machine learning approach improve prediction of differential brain activity pattern in patients with insomnia disorder.

Scientific reports
We investigated the differential spatial covariance pattern of blood oxygen level-dependent (BOLD) responses to single-task and multitask functional magnetic resonance imaging (fMRI) between patients with psychophysiological insomnia (PI) and healthy...

A Machine Learning Model Approach to Risk-Stratify Patients With Gastrointestinal Cancer for Hospitalization and Mortality Outcomes.

International journal of radiation oncology, biology, physics
PURPOSE: Patients with gastrointestinal (GI) cancer frequently experience unplanned hospitalizations, but predictive tools to identify high-risk patients are lacking. We developed a machine learning model to identify high-risk patients.

Computational medication regimen for Parkinson's disease using reinforcement learning.

Scientific reports
Our objective is to derive a sequential decision-making rule on the combination of medications to minimize motor symptoms using reinforcement learning (RL). Using an observational longitudinal cohort of Parkinson's disease patients, the Parkinson's P...

Distinguishing retinal angiomatous proliferation from polypoidal choroidal vasculopathy with a deep neural network based on optical coherence tomography.

Scientific reports
This cross-sectional study aimed to build a deep learning model for detecting neovascular age-related macular degeneration (AMD) and to distinguish retinal angiomatous proliferation (RAP) from polypoidal choroidal vasculopathy (PCV) using a convoluti...

COVID-CT-MD, COVID-19 computed tomography scan dataset applicable in machine learning and deep learning.

Scientific data
Novel Coronavirus (COVID-19) has drastically overwhelmed more than 200 countries affecting millions and claiming almost 2 million lives, since its emergence in late 2019. This highly contagious disease can easily spread, and if not controlled in a ti...