AIMC Topic: Humans

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Robotic Prostatectomy and Prostate Cancer-Related Medicaid Spending: Evidence from New York State.

Journal of general internal medicine
BACKGROUND: Robotic prostatectomy is a costly new technology, but the costs may be offset by changes in treatment patterns. The net effect of this technology on Medicaid spending has not been assessed.

Predicting the sorption efficiency of heavy metal based on the biochar characteristics, metal sources, and environmental conditions using various novel hybrid machine learning models.

Chemosphere
Heavy metals in water and wastewater are taken into account as one of the most hazardous environmental issues that significantly impact human health. The use of biochar systems with different materials helped significantly remove heavy metals in the ...

A novel artificial intelligence protocol to investigate potential leads for diabetes mellitus.

Molecular diversity
Dipeptidyl peptidase-4 (DPP4) is highly participated in regulating diabetes mellitus (DM), and inhibitors of DPP4 may act as potential DM drugs. Therefore, we performed a novel artificial intelligence (AI) protocol to screen and validate the potentia...

A spectral characteristic analysis method for distinguishing heavy metal pollution in crops: VMD-PCA-SVM.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Exploring the characteristics and types of heavy metal pollution in crops has important implications for food security and human health. In this study, a method for distinguishing heavy metal-polluted elements in corn leaves was proposed. Based on th...

Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data.

Korean journal of radiology
OBJECTIVE: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables.

Prediction of the duration needed to achieve culture negativity in patients with active pulmonary tuberculosis using convolutional neural networks and chest radiography.

Respiratory investigation
BACKGROUND: We aimed to predict the duration needed to achieve culture negativity in patients with active pulmonary tuberculosis using convolutional neural networks (CNNs) and chest radiography.