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Humans - AI Medical Compendium

AIMC Topic: Humans

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Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning.

PLoS computational biology
Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management, yet existing methods are often context-specific, require a long preparation time, and non-outbreak prediction remains understudied. To address this...

Machine-learning approaches to predict individualized treatment effect using a randomized controlled trial.

European journal of epidemiology
Recent advancements in machine learning (ML) for analyzing heterogeneous treatment effects (HTE) are gaining prominence within the medical and epidemiological communities, offering potential breakthroughs in the realm of precision medicine by enablin...

Face readers.

Science (New York, N.Y.)
Artificial intelligence is becoming better than humans at scanning animals' faces for signs of stress and pain. Are more complex emotions next?

Artificial intelligence for opportunistic osteoporosis screening with a Hounsfield Unit in chronic obstructive pulmonary disease patients.

Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry
INTRODUCTION: To investigate the accuracy of an artificial intelligence (AI) prototype in determining bone mineral density (BMD) in chronic obstructive pulmonary disease (COPD) patients using chest computed tomography (CT) scans.

Development of a Wearable Sleeve-Based System Combining Polymer Optical Fiber Sensors and an LSTM Network for Estimating Knee Kinematics.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This study presents a novel wearable solution integrating Polymer Optical Fiber (POF) sensors into a knee sleeve to monitor knee flexion/extension (F/E) patterns during walking. POF sensors offer advantages such as flexibility, light weight, and robu...

Revolutionizing e-health: the transformative role of AI-powered hybrid chatbots in healthcare solutions.

Frontiers in public health
INTRODUCTION: The integration of Artificial Intelligence (AI) in healthcare, particularly through hybrid chatbots, is reshaping the industry by enhancing service delivery, patient engagement, and clinical outcomes. These chatbots combine AI with huma...

Making sense of fossils and artefacts: a review of best practices for the design of a successful workflow for machine learning-assisted citizen science projects.

PeerJ
Historically, the extensive involvement of citizen scientists in palaeontology and archaeology has resulted in many discoveries and insights. More recently, machine learning has emerged as a broadly applicable tool for analysing large datasets of fos...

Robot-Assisted Gait Training in Older Patients with Comorbid Conditions: A Pilot Study.

Experimental aging research
PURPOSE: This study aimed to evaluate the efficacy of robot-assisted gait training (RAGT) in older patients with neurological gait disorder accompanied by various comorbidities.

Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT.

PloS one
PURPOSE: This study aims to explore the potential of non-contrast abdominal CT radiomics and deep learning models in accurately diagnosing fatty liver.

Table tennis coaching system based on a multimodal large language model with a table tennis knowledge base.

PloS one
UNLABELLED: Table tennis is one of the most popular sports in the world, and it plays a positive role in the overall development of people's physical and mental health. This study develops an AI table tennis coaching system using a Multimodal Large L...