COVID mortality prediction with machine learning methods: a systematic review and critical appraisal
More than a year has passed since the report of the first case of coronavirus disease 2019
(COVID), and increasing deaths continue to occur. Minimizing the time required for resource …
(COVID), and increasing deaths continue to occur. Minimizing the time required for resource …
Machine learning and big data provide crucial insight for future biomaterials discovery and research
Abstract Machine learning have been widely adopted in a variety of fields including
engineering, science, and medicine revolutionizing how data is collected, used, and stored …
engineering, science, and medicine revolutionizing how data is collected, used, and stored …
Short-term rockburst damage assessment in burst-prone mines: an explainable XGBOOST hybrid model with SCSO algorithm
Rockburst can cause significant damage to infrastructure and equipment, and pose a
substantial risk to the safety of mine workers. Effective prediction of short-term rockburst …
substantial risk to the safety of mine workers. Effective prediction of short-term rockburst …
Electricity theft detection in smart grids based on deep neural network
Electricity theft is a global problem that negatively affects both utility companies and
electricity users. It destabilizes the economic development of utility companies, causes …
electricity users. It destabilizes the economic development of utility companies, causes …
[HTML][HTML] An intelligent Medical Cyber–Physical System to support heart valve disease screening and diagnosis
Cardiovascular diseases are currently the major causes of death globally. Among the
strategies to prevent cardiovascular issues, the automated classification of heart sound …
strategies to prevent cardiovascular issues, the automated classification of heart sound …
Ensemble machine learning techniques using computer simulation data for wild blueberry yield prediction
HR Seireg, YMK Omar, FE Abd El-Samie… - IEEE …, 2022 - ieeexplore.ieee.org
Precision agriculture is a challenging task to achieve. Several studies have been conducted
to forecast agricultural yields using machine learning algorithms (MLA), but few studies have …
to forecast agricultural yields using machine learning algorithms (MLA), but few studies have …
Grading diabetic retinopathy using multiresolution based CNN
Diabetic Retinopathy (DR) refers to a medical condition that affects the eye; it occurs due to
diabetes, and, if not detected early on, results in a reduction of visual capacity and may even …
diabetes, and, if not detected early on, results in a reduction of visual capacity and may even …
[HTML][HTML] Fragment-based drug discovery by NMR. Where are the successes and where can it be improved?
LG Mureddu, GW Vuister - Frontiers in molecular biosciences, 2022 - frontiersin.org
Over the last century, the definitions of pharmaceutical drug and drug discovery have
changed considerably. Evolving from an almost exclusively serendipitous approach, drug …
changed considerably. Evolving from an almost exclusively serendipitous approach, drug …
Using phenotype risk scores to enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder
UK Biobank (UKB) is a key contributor in mental health genome-wide association studies
(GWAS) but only~ 31% of participants completed the Mental Health Questionnaire (“MHQ …
(GWAS) but only~ 31% of participants completed the Mental Health Questionnaire (“MHQ …
Psychological predictors of socioeconomic resilience amidst the COVID-19 pandemic: Evidence from machine learning.
What predicts cross-country differences in the recovery of socioeconomic activity from the
COVID-19 pandemic? To answer this question, we examined how quickly countries' …
COVID-19 pandemic? To answer this question, we examined how quickly countries' …