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Assessing Design Space for the Device-Circuit Codesign of Nonvolatile Memory-Based Compute-in-Memory Accelerators.
Nano Lett
January 2025
Corporate Research, TSMC, Hsinchu, 300-094, Taiwan.
Unprecedented penetration of artificial intelligence (AI) algorithms has brought about rapid innovations in electronic hardware, including new memory devices. Nonvolatile memory (NVM) devices offer one such attractive alternative with ∼2× density and data retention after powering off. Compute-in-memory (CIM) architectures further improve energy efficiency by fusing the computation operations with AI model storage.
View Article and Find Full Text PDFClinical Decision Support Using Speech Signal Analysis: Systematic Scoping Review of Neurological Disorders.
J Med Internet Res
January 2025
Knight Foundation of Computing & Information Sciences, Florida International University, Miami, FL, United States.
Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.
View Article and Find Full Text PDFIdentification of Use Cases, Target Groups, and Motivations Around Adopting Smart Speakers for Health Care and Social Care Settings: Scoping Review.
JMIR AI
January 2025
Faculty of Social Science, Ruhr University Bochum, Bochum, Germany.
Background: Conversational agents (CAs) are finding increasing application in health and social care, not least due to their growing use in the home. Recent developments in artificial intelligence, machine learning, and natural language processing have enabled a variety of new uses for CAs. One type of CA that has received increasing attention recently is smart speakers.
View Article and Find Full Text PDFEnrichRBP: an automated and interpretable computational platform for predicting and analyzing RNA-binding protein events.
Bioinformatics
January 2025
School of Artificial Intelligence, Jilin University, Jilin, China.
Motivation: Predicting RNA-binding proteins (RBPs) is central to understanding post-transcriptional regulatory mechanisms. Here, we introduce EnrichRBP, an automated and interpretable computational platform specifically designed for the comprehensive analysis of RBP interactions with RNA.
Results: EnrichRBP is a web service that enables researchers to develop original deep learning and machine learning architectures to explore the complex dynamics of RNA-binding proteins.
Ethical and Appropriate Use of Artificial Intelligence by Medical Learners: What We Should Not Forget?
Mil Med
January 2025
Department of Community Medicine, Dr. D Y Patil Medical College, Hospital and Research Centre, Dr. D Y Patil Vidyapeeth (Deemed to be University), Pune 411018, India.
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