AIMC Topic: Humans

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Influenza Screening via Deep Learning Using a Combination of Epidemiological and Patient-Generated Health Data: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Screening for influenza in primary care is challenging due to the low sensitivity of rapid antigen tests and the lack of proper screening tests.

Maximizing the Potential of Patient-Reported Assessments by Using the Open-Source Concerto Platform With Computerized Adaptive Testing and Machine Learning.

Journal of medical Internet research
Patient-reported assessments are transforming many facets of health care, but there is scope to modernize their delivery. Contemporary assessment techniques like computerized adaptive testing (CAT) and machine learning can be applied to patient-repor...

Measuring and Preventing COVID-19 Using the SIR Model and Machine Learning in Smart Health Care.

Journal of healthcare engineering
COVID-19 presents an urgent global challenge because of its contagious nature, frequently changing characteristics, and the lack of a vaccine or effective medicines. A model for measuring and preventing the continued spread of COVID-19 is urgently re...

A Novel Method for Sleep-Stage Classification Based on Sonification of Sleep Electroencephalogram Signals Using Wavelet Transform and Recurrent Neural Network.

European neurology
INTRODUCTION: Visual sleep-stage scoring is a time-consuming technique that cannot extract the nonlinear characteristics of electroencephalogram (EEG). This article presents a novel method for sleep-stage differentiation based on sonification of slee...

Artificial intelligence that determines the clinical significance of capsule endoscopy images can increase the efficiency of reading.

PloS one
Artificial intelligence (AI), which has demonstrated outstanding achievements in image recognition, can be useful for the tedious capsule endoscopy (CE) reading. We aimed to develop a practical AI-based method that can identify various types of lesio...

Kernel methods and their derivatives: Concept and perspectives for the earth system sciences.

PloS one
Kernel methods are powerful machine learning techniques which use generic non-linear functions to solve complex tasks. They have a solid mathematical foundation and exhibit excellent performance in practice. However, kernel machines are still conside...

The emerging role of artificial intelligence in multiple sclerosis imaging.

Multiple sclerosis (Houndmills, Basingstoke, England)
BACKGROUND: Computer-aided diagnosis can facilitate the early detection and diagnosis of multiple sclerosis (MS) thus enabling earlier interventions and a reduction in long-term MS-related disability. Recent advancements in the field of artificial in...

Trends in robotic surgery utilization across tertiary children's hospitals in the United States.

Surgical endoscopy
BACKGROUND: A growing number of tertiary children's hospitals are utilizing robotic surgical technology. We sought to characterize national trends in pediatric surgical robotic case utilization and related drivers.

The implications of emerging technology on military human performance research priorities.

Journal of science and medicine in sport
OBJECTIVES: To demonstrate the need for the military human performance research community to anticipate and evolve with the emergence of new and disruptive battlefield technologies that are changing the fundamental role of the human combatant.

Deep-Learning Resources for Studying Glycan-Mediated Host-Microbe Interactions.

Cell host & microbe
Glycans, the most diverse biopolymer, are shaped by evolutionary pressures stemming from host-microbe interactions. Here, we present machine learning and bioinformatics methods to leverage the evolutionary information present in glycans to gain insig...