Artificial Intelligence Medical Compendium

The precise, high-throughput characterization of graphene oxide (GO) is essential for its use in advanced technologies but is hindered by its inherent structural heterogeneity. Traditional techniques, such as atomic force microscopy, are too slow for... read more 

Escalating global freshwater scarcity demands more energy-efficient and sustainable brackish water reverse osmosis (BWRO) desalination. This study demonstrates how integrating high-fidelity Artificial Neural Network (ANN) surrogates with a robust Non... read more 

The problem of class imbalance refers to an uneven distribution of quantity among classes in a dataset, where some classes are significantly underrepresented compared to others. Class imbalance is also prevalent in graph-structured data. Graph neural... read more 

Multi-mode damage coupling in composite structures is a key factor preventing accurate classification of different damage types. To address this, this paper presents a damage classification framework for composite structures based on acoustic emissio... read more 

BACKGROUND: Patients receiving home parenteral nutrition (HPN) face complex challenges and increasingly seek support online, including generative artificial intelligence (AI) platforms like ChatGPT. This survey study compared ChatGPT with clinician r... read more 

Healthcare Ethics Consultants (HECs) can serve as a resource for facilitating values-based conversations for responsible integration of AI technologies that benefit patients, providers, and healthcare organizations. First, the paper describes the dif... read more 

AIMS: To determine the importance of 11 climate variables on pasture spore count of Pseudopithomyces chartarum, a risk indicator of facial eczema (FE), and to forecast spore counts in New Zealand until 2100, using longitudinal P. chartarum pasture sp... read more 

BACKGROUND: Non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant chemotherapy (NACT) followed by surgery represent an ideal clinical setting to identify prognostic factors. To date, major pathological response (MPR) and complete patholo... read more 

PURPOSE: To propose a spatio-temporal U-Net based network (4DST) that exploits both spatial and dynamic information while avoiding memory-intensive 4D convolutional layers for ASL-based non-contrast enhanced 4-dimensional MR angiography (4D MRA) vess... read more 

Bayesian integration is posited as a fundamental computational mechanism underlying multisensory integration, and feedforward neural networks have been proposed to instantiate optimal Bayesian integration (OBI). However, empirical and theoretical res... read more