[HTML][HTML] Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations
This paper proposes a novel framework for simulating the dynamics of beams on elastic
foundations. Specifically, partial differential equations modeling Euler–Bernoulli and …
foundations. Specifically, partial differential equations modeling Euler–Bernoulli and …
A deep neural network for operator learning enhanced by attention and gating mechanisms for long-time forecasting of tumor growth
Forecasting tumor progression and assessing the uncertainty of predictions play a crucial
role in clinical settings, especially for determining disease outlook and making informed …
role in clinical settings, especially for determining disease outlook and making informed …
Coagulo-Net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks
Blood coagulation, which involves a group of complex biochemical reactions, is a crucial
step in hemostasis to stop bleeding at the injury site of a blood vessel. Coagulation …
step in hemostasis to stop bleeding at the injury site of a blood vessel. Coagulation …
Fractional gradient optimized explainable convolutional neural network for Alzheimer's disease diagnosis
Alzheimer's is one of the brain syndromes that steadily affects the brain memory. The early
stage of Alzheimer's disease (AD) is referred to as mild cognitive impairment (MCI), and the …
stage of Alzheimer's disease (AD) is referred to as mild cognitive impairment (MCI), and the …
Treatment-aware diffusion probabilistic model for longitudinal MRI generation and diffuse glioma growth prediction
Q Liu, E Fuster-Garcia, IT Hovden… - … on Medical Imaging, 2025 - ieeexplore.ieee.org
Diffuse gliomas are malignant brain tumors that grow widespread through the brain. The
complex interactions between neoplastic cells and normal tissue, as well as the treatment …
complex interactions between neoplastic cells and normal tissue, as well as the treatment …
[HTML][HTML] Modeling free tumor growth: Discrete, continuum, and hybrid approaches to interpreting cancer development
D Singh, D Paquin - Mathematical Biosciences and Engineering, 2024 - aimspress.com
Tumor growth dynamics serve as a critical aspect of understanding cancer progression and
treatment response to mitigate one of the most pressing challenges in healthcare. The in …
treatment response to mitigate one of the most pressing challenges in healthcare. The in …
A systematic study of the performance of machine learning models on analyzing the association between semen quality and environmental pollutants
Human exposure to Phthalates, a family of chemicals primarily used to enhance the
flexibility and durability of plastics, could lead to a decline in semen quality. Extensive …
flexibility and durability of plastics, could lead to a decline in semen quality. Extensive …
Physics-informed deep learning for infectious disease forecasting
Accurate forecasting of contagious illnesses has become increasingly important to public
health policymaking, and better prediction could prevent the loss of millions of lives. To …
health policymaking, and better prediction could prevent the loss of millions of lives. To …
Geometry-aware framework for deep energy method: an application to structural mechanics with hyperelastic materials
Physics-Informed Neural Networks (PINNs) have gained considerable interest in diverse
engineering domains thanks to their capacity to integrate physical laws into deep learning …
engineering domains thanks to their capacity to integrate physical laws into deep learning …
A Comparative Analysis of ARX and ANFIS Models for Tumor Growth Prediction Under Single and Multi-agent Chemotherapy
SG Liliopoulos, GS Stavrakakis… - Anticancer Research, 2024 - ar.iiarjournals.org
Background/Aim: Despite the advances in oncology and cancer treatment over the past
decades, cancer remains one of the deadliest diseases. This study focuses on further …
decades, cancer remains one of the deadliest diseases. This study focuses on further …