Geriatrics

Biologically Enhanced Machine Learning Model to uncover Novel Gene-Drug Targets for Alzheimer's Disease.

Given the complexity and multifactorial nature of Alzheimer's disease, investigating potential drug-gene targets is imperative for developing effective therapies and advancing our understanding of the underlying mechanisms driving the disease. We present an explainable ML model that integrates the role and impact of gene interactions to drive the genomic variant feature selection. The model levera...

Uncovering Important Diagnostic Features for Alzheimer's, Parkinson's and Other Dementias Using Interpretable Association Mining Methods.

Alzheimer's Disease and Related Dementias (ADRD) afflict almost 7 million people in the USA alone. The majority of research in ADRD is conducted using post-mortem samples of brain tissue or carefully recruited clinical trial patients. While these resources are excellent, they suffer from lack of sex/gender, and racial/ethnic inclusiveness. Electronic Health Records (EHR) data has the potential to ...

A Machine Learning Model to Harmonize Volumetric Brain MRI Data for Quantitative Neuroradiologic Assessment of Alzheimer Disease.

Purpose To extend a previously developed machine learning algorithm for harmonizing brain volumetric data of individuals undergoing neuroradiologic as...

Diagnosis Osteoporosis Risk: Using Machine Learning Algorithms Among Fasa Adults Cohort Study (FACS).

INTRODUCTION: In Iran, the assessment of osteoporosis through tools like dual-energy X-ray absorptiometry poses significant challenges due to their hi...

A Multi-Label Deep Learning Model for Detailed Classification of Alzheimer's Disease.

BACKGROUND: Accurate diagnosis and classification of Alzheimer's disease (AD) are crucial for effective treatment and management. Traditional diagnost...

Unveiling the Immune Landscape of Delirium through Single-Cell RNA Sequencing and Machine Learning: Towards Precision Diagnosis and Therapy.

BACKGROUND: Postoperative delirium (POD) poses significant clinical challenges regarding its diagnosis and treatment. Identifying biomarkers that can ...

Artificial Intelligence Methods in Infection Biology Research.

Despite unprecedented achievements, the domain-specific application of artificial intelligence (AI) in the realm of infection biology was still in its...

All-Cause Mortality Risk in Elderly Patients with Femoral Neck and Intertrochanteric Fractures: A Predictive Model Based on Machine Learning.

INTRODUCTION: The aim of this study was to identify the influencing factors for all-cause mortality in elderly patients with intertrochanteric and fem...

Creating Chemiluminescence Signature Arrays Coupled with Machine Learning for Alzheimer's Disease Serum Diagnosis.

Although omics and multi-omics approaches are the most used methods to create signature arrays for liquid biopsy, the high cost of omics technologies ...

Fall Detection in Passenger Elevators using Intelligent Surveillance Camera Systems: An Application with YoloV8 Nano Model

Computer vision technology, which involves analyzing images and videos captured by cameras through deep learning algorithms, has significantly advan...

E2ED^2:Direct Mapping from Noise to Data for Enhanced Diffusion Models

Diffusion models have established themselves as the de facto primary paradigm in visual generative modeling, revolutionizing the field through remar...

IMAGINE: An 8-to-1b 22nm FD-SOI Compute-In-Memory CNN Accelerator With an End-to-End Analog Charge-Based 0.15-8POPS/W Macro Featuring Distribution-Aware Data Reshaping

Charge-domain compute-in-memory (CIM) SRAMs have recently become an enticing compromise between computing efficiency and accuracy to process sub-8b ...

Transformer-Based Wireless Capsule Endoscopy Bleeding Tissue Detection and Classification

Informed by the success of the transformer model in various computer vision tasks, we design an end-to-end trainable model for the automatic detecti...

An End-to-End Depth-Based Pipeline for Selfie Image Rectification

Portraits or selfie images taken from a close distance typically suffer from perspective distortion. In this paper, we propose an end-to-end deep le...

Future Success Prediction in Open-Vocabulary Object Manipulation Tasks Based on End-Effector Trajectories

This study addresses a task designed to predict the future success or failure of open-vocabulary object manipulation. In this task, the model is req...

Brain Ageing Prediction using Isolation Forest Technique and Residual Neural Network (ResNet)

Brain aging is a complex and dynamic process, leading to functional and structural changes in the brain. These changes could lead to the increased r...

Ligand identification in CryoEM and X-ray maps using deep learning.

MOTIVATION: Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffr...

Efficiently Serving Large Multimodal Models Using EPD Disaggregation

Large Multimodal Models (LMMs) extend Large Language Models (LLMs) by handling diverse inputs such as images, audio, and video, but at the cost of a...

Integrating Zero-Shot Classification to Advance Long COVID Literature: A Systematic Social Media-Centered Review

Long COVID continues to challenge public health by affecting a significant segment of individuals who have recovered from acute SARS-CoV-2 infection...

Video Is Worth a Thousand Images: Exploring the Latest Trends in Long Video Generation

An image may convey a thousand words, but a video composed of hundreds or thousands of image frames tells a more intricate story. Despite significan...