AIMC Topic: Machine Learning

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Topological data analysis of zebrafish patterns.

Proceedings of the National Academy of Sciences of the United States of America
Self-organized pattern behavior is ubiquitous throughout nature, from fish schooling to collective cell dynamics during organism development. Qualitatively these patterns display impressive consistency, yet variability inevitably exists within patter...

Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study.

Circulation. Heart failure
BACKGROUND: Implantable cardiac sensors have shown promise in reducing rehospitalization for heart failure (HF), but the efficacy of noninvasive approaches has not been determined. The objective of this study was to determine the accuracy of noninvas...

Using a machine learning approach to predict mortality in critically ill influenza patients: a cross-sectional retrospective multicentre study in Taiwan.

BMJ open
OBJECTIVES: Current mortality prediction models used in the intensive care unit (ICU) have a limited role for specific diseases such as influenza, and we aimed to establish an explainable machine learning (ML) model for predicting mortality in critic...

Exploring the Consistency of the Quality Scores with Machine Learning for Next-Generation Sequencing Experiments.

BioMed research international
BACKGROUND: Next-generation sequencing enables massively parallel processing, allowing lower cost than the other sequencing technologies. In the subsequent analysis with the NGS data, one of the major concerns is the reliability of variant calls. Alt...

Healthcare pathway discovery and probabilistic machine learning.

International journal of medical informatics
BACKGROUND AND PURPOSE: Healthcare pathways define the execution sequence of clinical activities as patients move through a treatment process, and they are critical for maintaining quality of care. The aim of this study is to combine healthcare pathw...

Label-Free Leukemia Monitoring by Computer Vision.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While there are a number of well-recognized prognostic biomarkers at diagnosis, the most powerful independent prognostic factor is the response of the leukemia to induction chemo...

Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study.

Journal of medical Internet research
BACKGROUND: Methylphenidate, a stimulant used to treat attention deficit hyperactivity disorder, has the potential to be used nonmedically, such as for studying and recreation. In an era when many people actively use social networking services, exper...

Computational Identification and Analysis of Ubiquinone-Binding Proteins.

Cells
Ubiquinone is an important cofactor that plays vital and diverse roles in many biological processes. Ubiquinone-binding proteins (UBPs) are receptor proteins that dock with ubiquinones. Analyzing and identifying UBPs via a computational approach will...

A Comprehensive Machine-Learning-Based Software Pipeline to Classify EEG Signals: A Case Study on PNES vs. Control Subjects.

Sensors (Basel, Switzerland)
The diagnosis of psychogenic nonepileptic seizures (PNES) by means of electroencephalography (EEG) is not a trivial task during clinical practice for neurologists. No clear PNES electrophysiological biomarker has yet been found, and the only tool ava...