Multi-Step-Ahead Rainfall-Runoff Modeling: Decision Tree-Based Clustering for Hybrid Wavelet Neural-Networks Modeling
This paper introduces a novel hybrid approach for predicting the rainfall-runoff (rr)
phenomenon across different data division scenarios (50%-50%, 60%-40%, and 75%-25%) …
phenomenon across different data division scenarios (50%-50%, 60%-40%, and 75%-25%) …
From interpretation to explanation: An analytical examination of deep neural network with linguistic rule-based model
A Toofani, L Singh, S Paul - Computers and Electrical Engineering, 2024 - Elsevier
Abstract The Deep Learning (DL) models stand out as one of the most popular and widely
adopted machine learning techniques across various applications, owing to their capability …
adopted machine learning techniques across various applications, owing to their capability …
Advancing Precision Medicine: A Review of Innovative In Silico Approaches for Drug Development, Clinical Pharmacology and Personalized Healthcare
L Marques, B Costa, M Pereira, A Silva, J Santos… - Pharmaceutics, 2024 - mdpi.com
The landscape of medical treatments is undergoing a transformative shift. Precision
medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and …
medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and …
A survey on advancements in image-text multimodal models: From general techniques to biomedical implementations
With the significant advancements of Large Language Models (LLMs) in the field of Natural
Language Processing (NLP), the development of image-text multimodal models has …
Language Processing (NLP), the development of image-text multimodal models has …
[HTML][HTML] A Comprehensive Review of Explainable AI for Disease Diagnosis
AA Biswas - Array, 2024 - Elsevier
Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare
sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited …
sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited …
Efficient learning in spiking neural networks
Spiking neural networks (SNNs) are a large class of neural model distinct from
'classical'continuous-valued networks such as multilayer perceptrons (MLPs). With event …
'classical'continuous-valued networks such as multilayer perceptrons (MLPs). With event …
Optimizing Rare Disease Gait Classification through Data Balancing and Generative AI: Insights from Hereditary Cerebellar Ataxia
The interpretability of gait analysis studies in people with rare diseases, such as those with
primary hereditary cerebellar ataxia (pwCA), is frequently limited by the small sample sizes …
primary hereditary cerebellar ataxia (pwCA), is frequently limited by the small sample sizes …
Beyond Amyloid: A Machine Learning-Driven Approach Reveals Properties of Potent GSK-3β Inhibitors Targeting Neurofibrillary Tangles
Current treatments for Alzheimer's disease (AD) focus on slowing memory and cognitive
decline, but none offer curative outcomes. This study aims to explore and curate the …
decline, but none offer curative outcomes. This study aims to explore and curate the …
Intra-Individual Variations in How Insulin Sensitivity Responds to Long-Term Exercise: Predictions by Machine Learning Based on Large-Scale Serum Proteomics
JK Viken, T Olsen, CAA Drevon, M Hjorth, KI Birkeland… - Metabolites, 2024 - mdpi.com
Physical activity is effective for preventing and treating type 2 diabetes, but some individuals
do not achieve metabolic benefits from exercise (“non-responders”). We investigated non …
do not achieve metabolic benefits from exercise (“non-responders”). We investigated non …
A Meta Algorithm for Interpretable Ensemble Learning: The League of Experts
Background. The importance of explainable artificial intelligence and machine learning
(XAI/XML) is increasingly being recognized, aiming to understand how information …
(XAI/XML) is increasingly being recognized, aiming to understand how information …