Practice Management

Staffing & Scheduling

Latest AI and machine learning research in staffing & scheduling for healthcare professionals.

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QFAL: Quantum Federated Adversarial Learning

Quantum federated learning (QFL) merges the privacy advantages of federated systems with the compu...

Generating patient cohorts from electronic health records using two-step retrieval-augmented text-to-SQL generation

Clinical cohort definition is crucial for patient recruitment and observational studies, yet trans...

TripCraft: A Benchmark for Spatio-Temporally Fine Grained Travel Planning

Recent advancements in probing Large Language Models (LLMs) have explored their latent potential a...

Partial Orders for Precise and Efficient Dynamic Deadlock Prediction

Deadlocks are a major source of bugs in concurrent programs. They are hard to predict, because the...

Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning

Deep learning models lack shift invariance, making them sensitive to input shifts that cause chang...

Arbitrary Volumetric Refocusing of Dense and Sparse Light Fields

A four-dimensional light field (LF) captures both textural and geometrical information of a scene ...

M2-omni: Advancing Omni-MLLM for Comprehensive Modality Support with Competitive Performance

We present M2-omni, a cutting-edge, open-source omni-MLLM that achieves competitive performance to...

Enhancing Hepatopathy Clinical Trial Efficiency: A Secure, Large Language Model-Powered Pre-Screening Pipeline

Background: Recruitment for cohorts involving complex liver diseases, such as hepatocellular carci...

M3DA: Benchmark for Unsupervised Domain Adaptation in 3D Medical Image Segmentation

Domain shift presents a significant challenge in applying Deep Learning to the segmentation of 3D ...

Mean-Shift Distillation for Diffusion Mode Seeking

We present mean-shift distillation, a novel diffusion distillation technique that provides a prova...

A Comprehensive Survey on the Trustworthiness of Large Language Models in Healthcare

The application of large language models (LLMs) in healthcare has the potential to revolutionize c...

Beyond Performance Scores: Directed Functional Connectivity as a Brain-Based Biomarker for Motor Skill Learning and Retention

Motor skill acquisition in fields like surgery, robotics, and sports involves learning complex tas...

PLPHP: Per-Layer Per-Head Vision Token Pruning for Efficient Large Vision-Language Models

Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across a range of m...

Mentoring Software in Education and Its Impact on Teacher Development: An Integrative Literature Review

Mentoring software is a pivotal innovation in addressing critical challenges in teacher developmen...

Lost in Transcription, Found in Distribution Shift: Demystifying Hallucination in Speech Foundation Models

Speech foundation models trained at a massive scale, both in terms of model and data size, result ...

Hardware-Software Co-Design for Accelerating Transformer Inference Leveraging Compute-in-Memory

Transformers have become the backbone of neural network architecture for most machine learning app...

CONSTRUCTA: Automating Commercial Construction Schedules in Fabrication Facilities with Large Language Models

Automating planning with LLMs presents transformative opportunities for traditional industries, ye...

Continual Quantization-Aware Pre-Training: When to transition from 16-bit to 1.58-bit pre-training for BitNet language models?

Large language models (LLMs) require immense resources for training and inference. Quantization, a...

SkyReels-A1: Expressive Portrait Animation in Video Diffusion Transformers

We present SkyReels-A1, a simple yet effective framework built upon video diffusion Transformer to...

AffectSRNet : Facial Emotion-Aware Super-Resolution Network

Facial expression recognition (FER) systems in low-resolution settings face significant challenges...

Mitigating the Impact of Prominent Position Shift in Drone-based RGBT Object Detection

Drone-based RGBT object detection plays a crucial role in many around-the-clock applications. Howe...

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