AIMC Topic: Machine Learning

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Benchmarking Molecular Feature Attribution Methods with Activity Cliffs.

Journal of chemical information and modeling
Feature attribution techniques are popular choices within the explainable artificial intelligence toolbox, as they can help elucidate which parts of the provided inputs used by an underlying supervised-learning method are considered relevant for a sp...

Recognition of Leaf Disease Using Hybrid Convolutional Neural Network by Applying Feature Reduction.

Sensors (Basel, Switzerland)
Agriculture is crucial to the economic prosperity and development of India. Plant diseases can have a devastating influence towards food safety and a considerable loss in the production of agricultural products. Disease identification on the plant is...

Bangla Sign Language (BdSL) Alphabets and Numerals Classification Using a Deep Learning Model.

Sensors (Basel, Switzerland)
A real-time Bangla Sign Language interpreter can enable more than 200 k hearing and speech-impaired people to the mainstream workforce in Bangladesh. Bangla Sign Language (BdSL) recognition and detection is a challenging topic in computer vision and ...

An explainable machine learning framework for lung cancer hospital length of stay prediction.

Scientific reports
This work introduces a predictive Length of Stay (LOS) framework for lung cancer patients using machine learning (ML) models. The framework proposed to deal with imbalanced datasets for classification-based approaches using electronic healthcare reco...

Machine learning algorithms as new screening approach for patients with endometriosis.

Scientific reports
Endometriosis-a systemic and chronic condition occurring in women of childbearing age-is a highly enigmatic disease with unresolved questions. While multiple biomarkers, genomic analysis, questionnaires, and imaging techniques have been advocated as ...

Comparison of different feature extraction methods for applicable automated ICD coding.

BMC medical informatics and decision making
BACKGROUND: Automated ICD coding on medical texts via machine learning has been a hot topic. Related studies from medical field heavily relies on conventional bag-of-words (BoW) as the feature extraction method, and do not commonly use more complicat...

PRCTC: a machine learning model for prediction of response to corticosteroid therapy in COVID-19 patients.

Aging
Corticosteroid has been proved to be one of the few effective treatments for COVID-19 patients. However, not all the patients were suitable for corticosteroid therapy. In this study, we aimed to propose a machine learning model to forecast the respon...

Uncharted Waters of Machine and Deep Learning for Surgical Phase Recognition in Neurosurgery.

World neurosurgery
Recent years have witnessed artificial intelligence (AI) make meteoric leaps in both medicine and surgery, bridging the gap between the capabilities of humans and machines. Digitization of operating rooms and the creation of massive quantities of dat...

Using Machine Learning to Identify Metabolomic Signatures of Pediatric Chronic Kidney Disease Etiology.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Untargeted plasma metabolomic profiling combined with machine learning (ML) may lead to discovery of metabolic profiles that inform our understanding of pediatric CKD causes. We sought to identify metabolomic signatures in pediatric CKD b...

Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

Rheumatology international
The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542 individuals with rheumatoid arthritis, or diabetes mellitu...