Latest AI and machine learning research in health policy for healthcare professionals.
Reinforcement learning demonstrated immense success in modelling complex physics-driven systems, providing end-to-end trainable solutions by interacting with a simulated or real environment, maximizing a scalar reward signal. In this work, we propose, building upon previous work, a multi-agent reinforcement learning approach with assignment constraints for reconstructing particle tracks in pixel...
Artificial intelligence (AI) technology is a scientific and technological field that focuses on the research and development of systems that simulate, extend, and expand human intelligence activities. This field encompasses various applications such as image recognition, language processing, expert systems, and robotics. The advancement of AI has greatly improved the quality and efficiency of medi...
Telecommunication technologies are important enablers for both digital and ecological transitions. By offering digital alternatives to traditional m...
Focussing on two different use cases-Quality Control methods in industrial contexts and Neural Network algorithms for healthcare diagnostics-this re...
The chapter discusses the foundational impact of modern generative AI models on information access (IA) systems. In contrast to traditional AI, the ...
For many practical applications, a high computational cost of inference over deep network architectures might be unacceptable. A small degradation i...
The rapid integration of artificial intelligence (AI) in healthcare is revolutionizing medical diagnostics, personalized medicine, and operational e...
This study examines the equity impacts of integrating shared autonomous mobility services (SAMS) into transit system redesign. Using the Greater Chi...
Root system architecture (RSA) is central to plant adaptation and fitness, yet the design principles and regulatory mechanisms connecting RSA to envir...
Alzheimer’s disease (AD) is characterized by region- and patient-specific molecular heterogeneity, which hinders therapeutic design. In this study, we...
Inspired by the success of large language models (LLMs) in natural language processing, cell language models (CLMs) have emerged as a promising paradi...
Social camouflaging refers to strategies to hide or compensate for social difficulties, often at a significant mental health cost, and is particularly...
Fertility is one of the major factors affecting the efficiency of dairy herd, and genomic selection (GS) on milk yield, while ignoring fertility, has ...
Identifying protein binding site residues is critical for understanding molecular interactions but challenging due to incomplete knowledge of features...
Creativity is central to human innovation, yet it often fluctuates from moment to moment. Identifying simple interventions to reliably boost creativit...
Quantifying animal behavior is pivotal for identifying the underlying neuronal and genetic mechanisms involved. Computational approaches have enabled ...
Protein structures are crucial in understanding function, mechanism and disease-causing variants of proteins within any living cell. A number of exper...
The development of flexible bioelectronics remains a complex, multidisciplinary process that demands specialized expertise and labor-intensive efforts...
Optimal diffusion MRI (dMRI) data for image denoising is often unavailable from scanner reconstruction. In this work, we make available an offline rec...
The current state of mental health treatment for individuals diagnosed with major depressive disorder leaves billions of individuals with first-line t...