Results 51 to 60 of about 137,842 (266)
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
To compare the performance of humans, GPT-4.0 and GPT-3.5 in answering multiple-choice questions from the American Academy of Ophthalmology (AAO) Basic and Clinical Science Course (BCSC) self-assessment program, available at https://www.aao.org/education/
Andrea Taloni +6 more
doaj +1 more source
GPT-PPG: a GPT-based foundation model for photoplethysmography signals
Abstract Objective. This study aims to introduce a novel generative pre-trained transformer (GPT)-based foundation model specifically tailored to photoplethysmography (PPG) signals, enabling effective adaptation to various downstream biomedical tasks. Approach.
Zhaoliang Chen +6 more
openaire +3 more sources
Adaptive 4D‐Printed Vascular Stents With Low‐Temperature‐Activated and Intelligent Deployment
Microarchitected coronary artery stents were fabricated using a polycaprolactone (PCL)‐based shape memory polymer (SMP) composite via projection micro‐stereolithography (PµSL) 4D printing. By incorporating diethyl phthalate (DEP) as a plasticizer, the thermal transition temperature (Ttran) was modulated to about 37°C, enabling rapid and autonomous ...
Yannan Li +12 more
wiley +1 more source
Continuity of the Green function in meromorphic families of polynomials
We prove that along any marked point the Green function of a meromorphic family of polynomials parameterized by the punctured unit disk explodes exponentially fast near the origin with a continuous error term.Comment: Modified references.
Favre, Charles, Gauthier, Thomas
core +1 more source
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley +1 more source
Generative artificial intelligence in graduate medical education
Generative artificial intelligence (GenAI) is rapidly transforming various sectors, including healthcare and education. This paper explores the potential opportunities and risks of GenAI in graduate medical education (GME).
Ravi Janumpally +3 more
doaj +1 more source
Key Features of GPT Learning Paradigm [PDF]
The continuous advancement of technology has always sparked debates, much like earlier shifts in history. From the introduction of computers in the mid-20th century to the rise of the internet in the 2000s, each innovation has brought both excitement and
Madalina Pana
doaj +1 more source
Amyloidogenic Peptide Fragments Designed From Bacterial Collagen‐like Proteins Form Hydrogel
This study identified amyloidogenic sequence motifs in bacterial collagen‐like proteins and exploited these to design peptides that self‐assemble into β‐sheet fibers and form hydrogels. One hydrogel supported healthy fibroblast growth, showing promise for biocompatible materials. Our work demonstrates that bacterial sequences can be harnessed to create
Vamika Sagar +5 more
wiley +1 more source
In the work reported herein, the catalytic effects of acid sites on electrocatalytic glycerol oxidation reaction are investigated by using a novel catalytic material system that integrates Pt metal sites with acidic Al sites. Abstract The catalytic role and function of acid sites in solid acid catalysts, such as zeolites, are well understood in the ...
Ju Ye Kim +11 more
wiley +1 more source

