Pain Management

Latest AI and machine learning research in pain management for healthcare professionals.

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Context-driven Missing-Modality Learning for Robust Medical Diagnosis with Image-Tabular Data

While multimodal data integrating diverse imaging and clinical tabular records is crucial for accura...

Multi-view Consistent 3D Gaussian Head Avatars 'without' Multi-view Generation

High-fidelity 3D Gaussian head avatar generation is critical for applications such as AR/VR, telepre...

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of A...

MASHA: A Multi-Agent System for Healthcare Sentiment Analysis Using AI for Migraine Detection in Arabic Tweets

Migraine detection and sentiment analysis in healthcare have become increasingly important, particul...

A Competitive Framework for Modeling EEG Microstate Durations

Background. This study examines a competition based model (Cmodel) designed to capture the temporal ...

Post-ED Trajectory Prediction in Abdominal Pain with a Generative Medical Event Model

Importance: Abdominal pain causes roughly 10 million US emergency department (ED) visits annually, m...

Widespread use of invalid statistical tests in biomedical machine learning

Machine learning is accelerating biomedical research. Cross-validation is widely used to compare pre...

Modeling Complex Effects and Individual Variability in Multi-Paradigm fMRI with Nonlinear Mixed Models

Functional magnetic resonance imaging (fMRI) data are inherently complex, characterized by high dime...

Transcript architecture predetermines m6A remodeling and sensory neuron vulnerability in chemotherapy-induced peripheral neuropathy

Whether individual transcripts carry intrinsic features that predetermine their response to external...

Artificial intelligence-generated digital Romberg test for peripheral neuropathy monitoring.

Background and Objectives Patients with peripheral neuropathies (PN) commonly exhibit balance impair...

AIM-DDI: A Model-Agnostic Multimodal Integration Module for Drug-Drug Interaction Prediction

Drug-drug interaction (DDI) prediction is a critical task in computational biomedicine, as adverse i...

SceneForge: Structured World Supervision from 3D Interventions

Many multimodal learning tasks require supervision that remains consistent across edits, viewpoints,...

CAWI: Copula-Aligned Weight Initialization for Randomized Neural Networks

Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing rando...

Images in Sentences: Scaling Interleaved Instructions for Unified Visual Generation

While recent advancements in multimodal language models have enabled image generation from expressiv...

Prompt-engineering improves clinical safety of large language models for opioid equipotency conversion

Background: Large language models (LLMs) are increasingly used in medical education and clinical dec...

A widespread internal brain state for fentanyl withdrawal

Opioid addiction is characterized by escalating drug use, driven in part by negative reinforcement f...

TRACED: In vivo imaging of extracellular intrinsic diffusivity, tortuosity, cell size distribution and cell density in human glioma patients

The lack of analytical models describing diffusion time dependence at intermediate time scales in co...

A biologically annotated neural network for proteomic discovery in Parkinsons disease

Machine learning models that can utilize high-dimensional data to make predictions and derive biolog...

Predicting one-year postoperative functional status in contrast-enhancing glioma

Background and Objectives Preoperative prediction of functional outcomes in contrast-enhancing gliom...

A Data-Centric Framework for Intraoperative Fluorescence Lifetime Imaging for Glioma Surgical Guidance

Accurate intraoperative assessment of glioma infiltration is essential for maximizing tumor resectio...

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