AIMC Topic: Machine Learning

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Predicting gait events from tibial acceleration in rearfoot running: A structured machine learning approach.

Gait & posture
BACKGROUND: Gait event detection of the initial contact and toe off is essential for running gait analysis, allowing the derivation of parameters such as stance time. Heuristic-based methods exist to estimate these key gait events from tibial acceler...

Machine Learning Enhanced Spectrum Recognition Based on Computer Vision (SRCV) for Intelligent NMR Data Extraction.

Journal of chemical information and modeling
A machine learning enhanced spectrum recognition system called spectrum recognition based on computer vision (SRCV) for data extraction from previously analyzed C and H NMR spectra has been developed. The intelligent system was designed with four fun...

Whether the weather will help us weather the COVID-19 pandemic: Using machine learning to measure twitter users' perceptions.

International journal of medical informatics
OBJECTIVE: The potential ability for weather to affect SARS-CoV-2 transmission has been an area of controversial discussion during the COVID-19 pandemic. Individuals' perceptions of the impact of weather can inform their adherence to public health gu...

SSP: Early prediction of sepsis using fully connected LSTM-CNN model.

Computers in biology and medicine
BACKGROUND: Sepsis is a life-threatening condition that occurs due to the body's reaction to infections, and it is a leading cause of morbidity and mortality in hospitals. Early prediction of sepsis onset facilitates early interventions that promote ...

Machine learning for psychiatry: getting doctors at the black box?

Molecular psychiatry
Recent developments in the field of machine learning have spurred high hopes for diagnostic support for psychiatric patients based on brain MRI. But while technical advances are undoubtedly remarkable, the current trajectory of mostly proof-of-concep...

Machine-learning algorithms for predicting hospital re-admissions in sickle cell disease.

British journal of haematology
Reducing preventable hospital re-admissions in Sickle Cell Disease (SCD) could potentially improve outcomes and decrease healthcare costs. In a retrospective study of electronic health records, we hypothesized Machine-Learning (ML) algorithms may out...

Association of a Serum Protein Signature With Rheumatoid Arthritis Development.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: The pathophysiologic events that precede the onset of rheumatoid arthritis (RA) remain incompletely understood. This study was undertaken to identify changes in the serum proteome that precede the onset of RA, with the aim of providing new...

Machine learning in classification and identification of nonconventional vegetables.

Journal of food science
Vegetables are important in economic, social, and nutritional matters in both the Brazilian and international scenes. Hence, some researches have been carried out in order to encourage the production and consumption of different species such as nonco...

H-RACS: a handy tool to rank anti-cancer synergistic drugs.

Aging
Though promising, identifying synergistic combinations from a large pool of candidate drugs remains challenging for cancer treatment. Due to unclear mechanism and limited confirmed cases, only a few computational algorithms are able to predict drug s...

Triage of documents containing protein interactions affected by mutations using an NLP based machine learning approach.

BMC genomics
BACKGROUND: Information on protein-protein interactions affected by mutations is very useful for understanding the biological effect of mutations and for developing treatments targeting the interactions. In this study, we developed a natural language...