AIMC Topic: Machine Learning

Clear Filters Showing 34221 to 34230 of 34417 articles

Tackling the problem of HIV drug resistance.

Postepy biochemii
The virally-encoded HIV-1 protease is an effective target for antiviral drugs, however, treatment for HIV infections is limited by the prevalence of drug resistant viral mutants. In this review, we describe our three-pronged approach to analyze and c...

Extraction of actionable information from crowdsourced disaster data.

Journal of emergency management (Weston, Mass.)
Natural disasters cause enormous damage to countries all over the world. To deal with these common problems, different activities are required for disaster management at each phase of the crisis. There are three groups of activities as follows: (1) m...

SAnDReS a Computational Tool for Statistical Analysis of Docking Results and Development of Scoring Functions.

Combinatorial chemistry & high throughput screening
BACKGROUND: Docking allows to predict ligand binding to proteins, since the 3D-structure for the target is available. Several docking studies have been carried out to identify potential ligands for drug targets. Many of these studies resulted in the ...

Classification of Movement of People with Parkinsons Disease Using Wearable Inertial Movement Units and Machine Learning.

Studies in health technology and informatics
In this work, inertial movement units were placed on people with Parkinsons disease (PwPD) who subsequently performed a standard test of walking endurance (six-minute walk test - 6MWT). Five devices were placed on each the limbs and small of the back...

Cheminformatics Based Machine Learning Approaches for Assessing Glycolytic Pathway Antagonists of Mycobacterium tuberculosis.

Combinatorial chemistry & high throughput screening
BACKGROUND: Tuberculosis is the second leading cause of death from an infectious disease worldwide after HIV, thus reasoning the expeditions in antituberculosis research. The rising number of cases of infection by resistant forms of M. tuberculosis h...

Bioimage Informatics for Big Data.

Advances in anatomy, embryology, and cell biology
Bioimage informatics is a field wherein high-throughput image informatics methods are used to solve challenging scientific problems related to biology and medicine. When the image datasets become larger and more complicated, many conventional image a...

Probing the Hypothesis of SAR Continuity Restoration by the Removal of Activity Cliffs Generators in QSAR.

Current pharmaceutical design
In this work we report the first attempt to study the effect of activity cliffs over the generalization ability of machine learning (ML) based QSAR classifiers, using as study case a previously reported diverse and noisy dataset focused on drug induc...

5-Year Trends in QSAR and its Machine Learning Methods.

Current computer-aided drug design
BACKGROUND: Quantitative Structure-Activity Relationships (QSAR) is a well-established branch of computational chemistry. The presence of QSAR papers is decreasing for the last few years.

Natural Language Understanding Performance & Use Considerations in Virtual Medical Encounters.

Studies in health technology and informatics
A virtual standardized patient (VSP) prototype was tested for natural language understanding (NLU) performance. The conversational VSP was evaluated in a controlled 61 subject study over four repetitions of a patient case. The prototype achieved more...