Contribution of molecular structures and quantum chemistry technique to root concentration factor: An innovative application of interpretable machine learning
T Zhu, Y Zhang, Y Li, T Tao, C Tao - Journal of Hazardous Materials, 2023 - Elsevier
Root concentration factor (RCF) is a significant parameter to characterize uptake and
accumulation of hazardous organic contaminants (HOCs) by plant roots. However, complex …
accumulation of hazardous organic contaminants (HOCs) by plant roots. However, complex …
Enhanced P&O MPPT Algorithm based on Fuzzy Logic for PV System: Brief Review and Experimental Implementation
CBN Fapı, H Tchakounté - International Journal of Engineering …, 2023 - dergipark.org.tr
The maximum power point tracking (MPPT) based perturbation and observation (P&O)
approach for photovoltaic (PV) devices is first created in this study after a survey of the …
approach for photovoltaic (PV) devices is first created in this study after a survey of the …
Application of QSAR models for acute toxicity of tetrazole compounds administrated orally and intraperitoneally in rat and mouse
Z Liu, J Gao, C Li, L Xu, X Lv, H Deng, Y Gao, H Wang… - Toxicology, 2023 - Elsevier
Tetrazoles and their derivatives possess various biological activities, such as antibacterial,
anti-fungal, and other activities. However, these compounds may induce specific cumulative …
anti-fungal, and other activities. However, these compounds may induce specific cumulative …
[HTML][HTML] Graph neural networks-enhanced relation prediction for ecotoxicology (GRAPE)
Exposure to toxic chemicals threatens species and ecosystems. This study introduces a
novel approach using Graph Neural Networks (GNNs) to integrate aquatic toxicity data …
novel approach using Graph Neural Networks (GNNs) to integrate aquatic toxicity data …
Investigating the effect of feature selection methods on the success of overall equipment effectiveness prediction
Overall equipment effectiveness (OEE) describes production efficiency by combining
availability, performance, and quality and is used to evaluate production equipment's …
availability, performance, and quality and is used to evaluate production equipment's …
[HTML][HTML] Advanced Detection of Abnormal ECG Patterns Using an Optimized LADTree Model with Enhanced Predictive Feature: Potential Application in CKD
M Binsawad, B Khan - Algorithms, 2024 - mdpi.com
Detecting abnormal ECG patterns is a crucial area of study aimed at enhancing diagnostic
accuracy and enabling early identification of Chronic Kidney Disease (CKD)-related …
accuracy and enabling early identification of Chronic Kidney Disease (CKD)-related …
Integrating machine learning and high throughput screening for the discovery of allosteric AKT1 inhibitors
K Karunakaran, R Muniyan - Journal of Biomolecular Structure and …, 2023 - Taylor & Francis
Evidence from clinical and experimental investigations reveals the role of AKT in oral
cancer, which has led to the development of therapeutic and pharmacological medications …
cancer, which has led to the development of therapeutic and pharmacological medications …
Performance Analysis Of Machine Learning-Based Models For Early Diagnosis Of Obesity Using Blood Test Parameters
SN Cuhadar, G Karaduman, A Uyanik… - International Journal of …, 2023 - dergipark.org.tr
Obesity is a global health issue that continues to grow, with projections indicating further
increases in obesity rates. The World Health Organization defines overweight and obesity as …
increases in obesity rates. The World Health Organization defines overweight and obesity as …
Early Diagnoses of Acute Coroner Syndrome Based on Machine Learning Model
UU Tiryaki, G Karaduman, SN Cuhadar… - … of Engineering and …, 2024 - dergipark.org.tr
Cardiovascular diseases are a leading global cause of death, particularly in low to middle-
income countries. Early and accurate diagnosis of Acute Coronary Syndrome (ACS) is vital …
income countries. Early and accurate diagnosis of Acute Coronary Syndrome (ACS) is vital …