AIMC Topic: Machine Learning

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Predicting post-stroke activities of daily living through a machine learning-based approach on initiating rehabilitation.

International journal of medical informatics Jan 4, 2018
OBJECTIVES: Prediction of activities of daily living (ADL) is crucial for optimized care of post-stroke patients. However, no suitably-validated and practical models are currently available in clinical practice.
Stroke Rehabilitation Decision Making, Computer-Assisted Patient Discharge Stroke Activities of Daily Living Male Middle Aged Taiwan Humans Retrospective Studies Machine Learning Female Algorithms Aged
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Preliminary investigation of human exhaled breath for tuberculosis diagnosis by multidimensional gas chromatography - Time of flight mass spectrometry and machine learning.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences Jan 4, 2018
Tuberculosis (TB) remains a global public health malady that claims almost 1.8 million lives annually. Diagnosis of TB represents perhaps one of the most challenging aspects of tuberculosis control. Gold standards for diagnosis of active TB (culture ...
Breath Tests Tuberculosis Gas Chromatography-Mass Spectrometry Volatile Organic Compounds Male Middle Aged Adolescent Humans Machine Learning Female Young Adult Adult
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Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features.

Computers in biology and medicine Jan 3, 2018
Liver is the heaviest internal organ of the human body and performs many vital functions. Prolonged cirrhosis and fatty liver disease may lead to the formation of benign or malignant lesions in this organ, and an early and reliable evaluation of thes...
Humans Machine Learning Female Adult Liver Cirrhosis Ultrasonography Male Liver Neoplasms Middle Aged Image Processing, Computer-Assisted Diagnosis, Computer-Assisted
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A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.

Nature communications Jan 3, 2018
Cancers that appear pathologically similar often respond differently to the same drug regimens. Methods to better match patients to drugs are in high demand. We demonstrate a promising approach to identify robust molecular markers for targeted treatm...
Humans Biomarkers, Tumor Leukemia, Myeloid, Acute Antineoplastic Agents Machine Learning Algorithms Precision Medicine Etoposide Topoisomerase II Inhibitors Cell Line DNA Helicases Datasets as Topic Nuclear Proteins Drug Resistance, Neoplasm Transcription Factors
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Machine learning: supervised methods.

Nature methods Jan 3, 2018
Supervised learning algorithms extract general principles from observed examples guided by a specific prediction objective.
Artificial Intelligence Machine Learning Support Vector Machine Humans
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Machine-learning neuroimaging challenge for automated diagnosis of mild cognitive impairment: Lessons learnt.

Journal of neuroscience methods Jan 2, 2018
Pattern Recognition, Automated Neuroimaging Cognitive Dysfunction Alzheimer Disease Image Interpretation, Computer-Assisted Humans Machine Learning Databases, Factual Brain Disease Progression
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VAMPnets for deep learning of molecular kinetics.

Nature communications Jan 2, 2018
There is an increasing demand for computing the relevant structures, equilibria, and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high-throughput molecular dynamics simulations. Current methods employ transfor...
Neural Networks, Computer Protein Folding Machine Learning Kinetics Molecular Dynamics Simulation Algorithms Markov Chains Protein Binding
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Sleep in patients with disorders of consciousness characterized by means of machine learning.

PloS one Jan 2, 2018
Sleep has been proposed to indicate preserved residual brain functioning in patients suffering from disorders of consciousness (DOC) after awakening from coma. However, a reliable characterization of sleep patterns in this clinical population continu...
Humans Machine Learning Middle Aged Sleep Consciousness Disorders Female Adult Male
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Gene ontology concept recognition using named concept: understanding the various presentations of the gene functions in biomedical literature.

Database : the journal of biological databases and curation Jan 1, 2018
OBJECTIVE: A major challenge in precision medicine is the development of patient-specific genetic biomarkers or drug targets. The firsthand information of the genes associated with the pathologic pathways of interest is buried in the ocean of biomedi...
Semantics Machine Learning Reproducibility of Results Gene Ontology Algorithms Biomedical Research Publications
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Large-scale automated machine reading discovers new cancer-driving mechanisms.

Database : the journal of biological databases and curation Jan 1, 2018
PubMed, a repository and search engine for biomedical literature, now indexes >1 million articles each year. This exceeds the processing capacity of human domain experts, limiting our ability to truly understand many diseases. We present Reach, a sys...
Publications Humans Automation Machine Learning Algorithms Neoplasms
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