AIMC Topic: Machine Learning

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Deep Learning in Radiology: Does One SizeĀ Fit All?

Journal of the American College of Radiology : JACR
Deep learning (DL) is a popular method that is used to perform many important tasks in radiology and medical imaging. Some forms of DL are able to accurately segment organs (essentially, trace the boundaries, enabling volume measurements or calculati...

Machine learning prioritizes synthesis of primaquine ureidoamides with high antimalarial activity and attenuated cytotoxicity.

European journal of medicinal chemistry
Primaquine (PQ) is a commonly used drug that can prevent the transmission of Plasmodium falciparum malaria, however toxicity limits its use. We prepared five groups of PQ derivatives: amides 1a-k, ureas 2a-k, semicarbazides 3a,b, acylsemicarbazides 4...

Natural Language-based Machine Learning Models for the Annotation of Clinical Radiology Reports.

Radiology
Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in these reports. Materials and Methods In this study, 96 303 head computed tomography (CT) reports were ob...

Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning.

Journal of medical Internet research
BACKGROUND: As a high-prevalence health condition, hypertension is clinically costly, difficult to manage, and often leads to severe and life-threatening diseases such as cardiovascular disease (CVD) and stroke.

Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm.

Physics in medicine and biology
In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally ...

Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms.

Computational and mathematical methods in medicine
We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs) and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or si...

Machine learning to parse breast pathology reports in Chinese.

Breast cancer research and treatment
INTRODUCTION: Large structured databases of pathology findings are valuable in deriving new clinical insights. However, they are labor intensive to create and generally require manual annotation. There has been some work in the bioinformatics communi...

Machine Learning Approaches for Clinical Psychology and Psychiatry.

Annual review of clinical psychology
Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an access...