Public Health & Policy

Work Force

Latest AI and machine learning research in work force for healthcare professionals.

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Artificial intelligence for skin cancer detection and classification for clinical environment: a systematic review.

BACKGROUND: Skin cancer is one of the most common forms worldwide, with a significant increase in in...

Using artificial intelligence to create diverse and inclusive medical case vignettes for education.

AIMS: Medical case vignettes play a crucial role in medical education, yet they often fail to authen...

Automated artificial intelligence-based phase-recognition system for esophageal endoscopic submucosal dissection (with video).

BACKGROUND AND AIMS: Endoscopic submucosal dissection (ESD) for superficial esophageal cancer is a m...

DeBERTa-BiLSTM: A multi-label classification model of Arabic medical questions using pre-trained models and deep learning.

It is wise to investigate past and present epidemics in the hopes of profiting from them and being b...

Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology.

INTRODUCTION: Artificial intelligence (AI)-based technologies embody countless solutions in radiatio...

The emergence of machine learning force fields in drug design.

In the field of molecular simulation for drug design, traditional molecular mechanic force fields an...

The impact of transitive annotation on the training of taxonomic classifiers.

INTRODUCTION: A common task in the analysis of microbial communities involves assigning taxonomic la...

Seeing Is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability.

We introduce Brain-Inspired Modular Training (BIMT), a method for making neural networks more modula...

: A Python Package for Measuring The Composition of Complex Datasets.

Machine-learning datasets are typically characterized by measuring their size and class balance. How...

Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning.

We propose DiRL, a Diversity-inducing Representation Learning technique for histopathology imaging. ...

Symptomatic hypercalcemia in an infant secondary to excessive consumption of almond milk as a formula alternative.

A 4-month-old previously healthy female presented with persistent nonbloody, nonbilious emesis, decr...

Gynecologic Surgical Subspecialty Training Decreases Surgical Complications in Benign Minimally Invasive Hysterectomy.

STUDY OBJECTIVE: To evaluate the impact of gynecologic subspecialty training on surgical outcomes in...

Mapping Cell Atlases at the Single-Cell Level.

Recent advancements in single-cell technologies have led to rapid developments in the construction o...

Multitype Perception Method for Drug-Target Interaction Prediction.

With the growing popularity of artificial intelligence in drug discovery, many deep-learning technol...

AI-powered real-time annotations during urologic surgery: The future of training and quality metrics.

INTRODUCTION AND OBJECTIVE: Real-time artificial intelligence (AI) annotation of the surgical field ...

Resistive versus active assisted robotic training for the upper limb after a stroke: A randomized controlled study.

BACKGROUND: Selection of a suitable training modality according to the status of upper limb function...

Training Universal Deep-Learning Networks for Electromagnetic Medical Imaging Using a Large Database of Randomized Objects.

Deep learning has become a powerful tool for solving inverse problems in electromagnetic medical ima...

Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning.

Developing robust artificial intelligence (AI) models that generalize well to unseen datasets is cha...

ChatGPT and Clinical Training: Perception, Concerns, and Practice of Pharm-D Students.

BACKGROUND: The emergence of Chat-Generative Pre-trained Transformer (ChatGPT) by OpenAI has revolut...

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