AIMC Topic: Machine Learning

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Practical Guide to Natural Language Processing for Radiology.

Radiographics : a review publication of the Radiological Society of North America, Inc
Natural language processing (NLP) is the subset of artificial intelligence focused on the computer interpretation of human language. It is an invaluable tool in the analysis, aggregation, and simplification of free text. It has already demonstrated s...

Deep Learning: An Update for Radiologists.

Radiographics : a review publication of the Radiological Society of North America, Inc
Deep learning is a class of machine learning methods that has been successful in computer vision. Unlike traditional machine learning methods that require hand-engineered feature extraction from input images, deep learning methods learn the image fea...

A Role for Prior Knowledge in Statistical Classification of the Transition from Mild Cognitive Impairment to Alzheimer's Disease.

Journal of Alzheimer's disease : JAD
BACKGROUND: The transition from mild cognitive impairment (MCI) to dementia is of great interest to clinical research on Alzheimer's disease and related dementias. This phenomenon also serves as a valuable data source for quantitative methodological ...

Trends in Deep Learning for Property-driven Drug Design.

Current medicinal chemistry
It is more pressing than ever to reduce the time and costs for the development of lead compounds in the pharmaceutical industry. The co-occurrence of advances in high-throughput screening and the rise of deep learning (DL) have enabled the developmen...

Identification of Blood-Based Glycolysis Gene Associated with Alzheimer's Disease by Integrated Bioinformatics Analysis.

Journal of Alzheimer's disease : JAD
BACKGROUND: Alzheimer's disease (AD) is one of many common neurodegenerative diseases without ideal treatment, but early detection and intervention can prevent the disease progression.

Clinical Trials and Machine Learning: Regulatory Approach Review.

Reviews on recent clinical trials
Machine Learning, a fast-growing technology, is an application of Artificial Intelligence that has provided important contributes to drug discovery and clinical development. In the last few years, the number of clinical applications based on Machine ...

Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A Review.

Current medical imaging
BACKGROUND: This paper provides a systematic review of the application of Artificial Intelligence (AI) in the form of Machine Learning (ML) and Deep Learning (DL) techniques in fighting against the effects of novel coronavirus disease (COVID-19).

Identification of Gene Regulatory Networks from Single-Cell Expression Data.

Methods in molecular biology (Clifton, N.J.)
Single-cell RNAseq is an emerging technology that allows the quantification of gene expression in individual cells. In plants, single-cell sequencing technology has been applied to generate root cell expression maps under many experimental conditions...

[Behavioral analysis with machine learning].

Nihon yakurigaku zasshi. Folia pharmacologica Japonica

Relevance of Complaint Severity in Predicting the Progression of Subjective Cognitive Decline and Mild Cognitive Impairment: A Machine Learning Approach.

Journal of Alzheimer's disease : JAD
BACKGROUND: The presence of subjective cognitive complaints (SCCs) is a core criterion for diagnosis of subjective cognitive decline (SCD); however, no standard procedure for distinguishing normative and non-normative SCCs has yet been established.