Results 211 to 220 of about 398,815 (273)

Expert-Designed Fact Sheets and AI-Based Analysis of Patient Symptoms to Combat Diagnostic Delays in Inherited Metabolic Diseases. [PDF]

J Inherit Metab Dis
Cano A, Chen X, Khemiri A, Brassier A, Jean-Baptiste A, Froissart R, Bouchereau J, Hoebeke C, Mazodier K, Héron B, Labrune P, Caillaud C, Cheillan D, Nadjar Y, Pichard S, Imbard A, Pettazzoni M, Douillard C, Nadia B, Calatayud AL, Zerguini M, Garcelon N, Benoist JF, Acquaviva C, De Lonlay P, other members of the expert group consortium.   +25 more
europepmc   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

Psychiatric Medications Procurement at Primary Health Centers (PHCs) in Tumkur: Insights from an Effectiveness Implementation Hybrid Randomized Controlled Trial on Mental Health Tele-mentoring of Primary Care Doctors (PCDs). [PDF]

Indian J Psychol Med
Hegde PR, Paul M, Subramaniyan SS, Sabhahit GG, Patley R, Das N, Parthasarathy R, Manjunatha N, Kumar CN, Math SB, Thirthalli J.   +10 more
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Algorithm Improvements in an Insertable Cardiac Monitor Reduce False Positives and Episode Review Burden. [PDF]

Pacing Clin Electrophysiol
Richards M, Kupfer M, Herrmann K, Mahajan D, Perschbacher D, Rajan A, Ravikumar V, Burke M.   +7 more
europepmc   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Chromosome-level genome assembly of the dwarf cattail Typha minima. [PDF]

Sci Data
Du J, Huang L, Xu X.
europepmc   +1 more source

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Advanced Intelligent Discovery, EarlyView.
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula, Lynnicia N. Massenburg, Spenser R. Brown, Amber N. Bible, Chanda R. Harris, Lance X. Zhang, Kiara Parker, Scott T. Retterer, Jennifer L. Morrell‐Falvey, Rama K. Vasudevan, Alexis N. Williams   +10 more
wiley   +1 more source

A mathematical modelling for integrated construction and production supply chain network design. [PDF]

Sci Rep
Helli SS, Mokhtari H, Dehnavi S.
europepmc   +1 more source