AIMC Topic: Machine Learning

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Glaucoma Diagnosis with Machine Learning Based on Optical Coherence Tomography and Color Fundus Images.

Journal of healthcare engineering
This study aimed to develop a machine learning-based algorithm for glaucoma diagnosis in patients with open-angle glaucoma, based on three-dimensional optical coherence tomography (OCT) data and color fundus images. In this study, 208 glaucomatous an...

MoDeSuS: A Machine Learning Tool for Selection of Molecular Descriptors in QSAR Studies Applied to Molecular Informatics.

BioMed research international
The selection of the most relevant molecular descriptors to describe a target variable in the context of QSAR (Quantitative Structure-Activity Relationship) modelling is a challenging combinatorial optimization problem. In this paper, a novel softwar...

Time-dependent AI-Modeling of the anticancer efficacy of synthesized gallic acid analogues.

Computational biology and chemistry
BACKGROUND/AIM: Main objective of this study is mapping of the anticancer efficacy of synthesized gallic acid analogues using modeling and artificial intelligence (AI) over a large range of concentrations and exposure times to explore the underline m...

Outcome prediction with serial neuron-specific enolase and machine learning in anoxic-ischaemic disorders of consciousness.

Computers in biology and medicine
BACKGROUND: The continuation of life-sustaining therapy in critical care patients with anoxic-ischemic disorders of consciousness (AI-DOC) depends on prognostic tests such as serum neuron-specific enolase (NSE) concentration levels.

Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data.

International journal of computer assisted radiology and surgery
PURPOSE: Cancers are almost always diagnosed by morphologic features in tissue sections. In this context, machine learning tools provide new opportunities to describe tumor immune cell interactions within the tumor microenvironment and thus provide p...

Deep neural networks in psychiatry.

Molecular psychiatry
Machine and deep learning methods, today's core of artificial intelligence, have been applied with increasing success and impact in many commercial and research settings. They are powerful tools for large scale data analysis, prediction and classific...

Design and Implementation of a Novel Subject-Specific Neurofeedback Evaluation and Treatment System.

Annals of biomedical engineering
Electroencephalography (EEG)-based neurofeedback (NF) is a safe, non-invasive, non-painful method for treating various conditions. Current NF systems enable the selection of only one NF parameter, so that two parameters cannot be feedback simultaneou...

Cross-Device Computation Coordination for Mobile Collocated Interactions with Wearables.

Sensors (Basel, Switzerland)
Mobile devices, wearables and Internet-of-Things are crammed into smaller form factors and batteries, yet they encounter demanding applications such as big data analysis, data mining, machine learning, augmented reality and virtual reality. To meet s...

Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data.

Journal of medical Internet research
BACKGROUND: Prevention and management of chronic diseases are the main goals of national health maintenance programs. Previously widely used screening tools, such as Health Risk Appraisal, are restricted in their achievement this goal due to their li...