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Multimodal cross-scale context clusters for classification of mental disorders using functional and structural MRI.
Neural Netw
January 2025
The Key Laboratory for Computer Systems of State Ethnic Affairs Commission, Southwest Minzu University, Chengdu, Sichuan 610225, China. Electronic address:
The brain is a complex system with multiple scales and hierarchies, making it challenging to identify abnormalities in individuals with mental disorders. The dynamic segregation and integration of activities across brain regions enable flexible switching between local and global information processing modes. Modeling these scale dynamics within and between brain regions can uncover hidden correlates of brain structure and function in mental disorders.
View Article and Find Full Text PDFAdvancing newborn care: Precise time of birth detection using ai-driven thermal imaging with adaptive normalization.
Comput Biol Med
January 2025
Dept. Electrical Engineering and Computer Science, University of Stavanger, Kristine Bonnevies vei 22, Stavanger, 4021, Rogaland, Norway.
Around 5%-10% of newborns need assistance to start breathing. Currently, there is a lack of evidence-based research, objective data collection, and opportunities for learning from real newborn resuscitation emergency events. Generating and evaluating automated newborn resuscitation algorithm activity timelines relative to the Time of Birth (ToB) offers a promising opportunity to enhance newborn care practices.
View Article and Find Full Text PDFCancer drug resistance as learning of signaling networks.
Biomed Pharmacother
January 2025
Department of Molecular Biology, Semmelweis University, Budapest, Hungary. Electronic address:
Drug resistance is a major cause of tumor mortality. Signaling networks became useful tools for driving pharmacological interventions against cancer drug resistance. Signaling datasets now cover the entire human cell.
View Article and Find Full Text PDFDistinguishing classes of neuroactive drugs based on computational physicochemical properties and experimental phenotypic profiling in planarians.
PLoS One
January 2025
Department of Biology, Swarthmore College, Swarthmore, Pennsylvania, United States of America.
Mental illnesses put a tremendous burden on afflicted individuals and society. Identification of novel drugs to treat such conditions is intrinsically challenging due to the complexity of neuropsychiatric diseases and the need for a systems-level understanding that goes beyond single molecule-target interactions. Thus far, drug discovery approaches focused on target-based in silico or in vitro high-throughput screening (HTS) have had limited success because they cannot capture pathway interactions or predict how a compound will affect the whole organism.
View Article and Find Full Text PDFSineKAN: Kolmogorov-Arnold Networks using sinusoidal activation functions.
Front Artif Intell
January 2025
Department of Physics and Astronomy, The University of Alabama, Tuscaloosa, AL, United States.
Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation functions on the edges of the computational graph followed by summation on nodes. The learnable edge activation functions in the original implementation are basis spline functions (B-Spline).
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