Machine learning-based design and monitoring of algae blooms: Recent trends and future perspectives–A short review
Abstract Machine learning (ML) models are widely used methods for analyzing data from
sensors and satellites to monitor climate change, predict natural disasters, and protect …
sensors and satellites to monitor climate change, predict natural disasters, and protect …
[HTML][HTML] Evaluating the risk of endometriosis based on patients' self-assessment questionnaires
K Zieliński, D Drabczyk, M Kunicki, D Drzyzga… - Reproductive Biology …, 2023 - Springer
Background Endometriosis is a condition that significantly affects the quality of life of about
10% of reproductive-aged women. It is characterized by the presence of tissue similar to the …
10% of reproductive-aged women. It is characterized by the presence of tissue similar to the …
[HTML][HTML] An integrated data mining algorithms and meta-heuristic technique to predict the readmission risk of diabetic patients
M Zeinalnezhad, S Shishehchi - Healthcare Analytics, 2024 - Elsevier
Reducing hospital readmission rate is a significant challenge in the healthcare industry for
managers and policymakers seeking to improve healthcare and lower costs. This study …
managers and policymakers seeking to improve healthcare and lower costs. This study …
Improvement of Classification Accuracy in Machine Learning Algorithm by Hyper-Parameter Optimization
SS Pandi, VR Chiranjeevi… - 2023 International …, 2023 - ieeexplore.ieee.org
The manual optimization of hyperparameters is a straightforward and well-known approach,
but it is not scalable, particularly when there are several settings and options. In nearly every …
but it is not scalable, particularly when there are several settings and options. In nearly every …
Accuracy and Performance of Machine Learning Methodologies: Novel Assessments of Country Pandemic Vulnerability Based on Non-Pandemic Predictors
MM Vlajnic, SJ Simske - IEEE Access, 2023 - ieeexplore.ieee.org
The devastating effects of the COVID-19 pandemic created a need for sensitive and
accurate machine learning methodologies for assessment of predictors of pandemic …
accurate machine learning methodologies for assessment of predictors of pandemic …
[HTML][HTML] Estimation of Anthocyanins in Winter Wheat Based on Band Screening Method and Genetic Algorithm Optimization Models
H Miao, X Chen, Y Guo, Q Wang, R Zhang, Q Chang - Remote Sensing, 2024 - mdpi.com
Anthocyanin can improve the stress tolerance and disease resistance of winter wheat to a
certain extent, so timely and accurate monitoring of anthocyanin content is crucial for the …
certain extent, so timely and accurate monitoring of anthocyanin content is crucial for the …
CODE FOR CARE: HYPERTENSION PREDICTION IN WOMEN AGED 18-39 YEARS
K Sheth - 2024 - scholarworks.lib.csusb.edu
The longstanding prevalence of hypertension, often undiagnosed, poses significant risks of
severe chronic and cardiovascular complications if left untreated. This study investigated the …
severe chronic and cardiovascular complications if left untreated. This study investigated the …
Advancing Alzheimer's Disease Risk Prediction: Development and Validation of a Machine Learning-Based Preclinical Screening Model
L Chen, A Shi, W Qi, J Yao, C Dong, X Zhu, B Wang… - 2023 - researchsquare.com
Background: Alzheimer's disease (AD) poses a significant challenge for individuals aged 65
and older, being the most prevalent form of dementia. Most existing Alzheimer's disease risk …
and older, being the most prevalent form of dementia. Most existing Alzheimer's disease risk …