AIMC Topic: Humans

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Machine learning enabled subgroup analysis with real-world data to inform clinical trial eligibility criteria design.

Scientific reports
Overly restrictive eligibility criteria for clinical trials may limit the generalizability of the trial results to their target real-world patient populations. We developed a novel machine learning approach using large collections of real-world data ...

Decoding of human identity by computer vision and neuronal vision.

Scientific reports
Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity...

Self-vectoring electromagnetic soft robots with high operational dimensionality.

Nature communications
Soft robots capable of flexible deformations and agile locomotion similar to biological systems are highly desirable for promising applications, including safe human-robot interactions and biomedical engineering. Their achievable degree of freedom an...

Identify Hard-to-Place Kidneys for Early Engagement in Accelerated Placement With a Deep Learning Optimization Approach.

Transplantation proceedings
Recommended practices that follow match-run sequences for hard-to-place kidneys succumb to many declines, accruing cold ischemic time and exacerbating kidney quality that may lead to unnecessary kidney discard. Hard-to-place deceased donor kidneys ac...

Emotional Variance Analysis: A new sentiment analysis feature set for Artificial Intelligence and Machine Learning applications.

PloS one
Sentiment Analysis (SA) is a category of data mining techniques that extract latent representations of affective states within textual corpuses. This has wide ranging applications from online reviews to capturing mental states. In this paper, we pres...

Prediction of Visual Impairment in Epiretinal Membrane and Feature Analysis: A Deep Learning Approach Using Optical Coherence Tomography.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: The aim was to develop a deep learning model for predicting the extent of visual impairment in epiretinal membrane (ERM) using optical coherence tomography (OCT) images, and to analyze the associated features.

Estimation of a Machine Learning-Based Decision Rule to Reduce Hypoglycemia Among Older Adults With Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM Study.

Journal of diabetes science and technology
BACKGROUND: The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated continuous glucose monitoring (CGM) reduced hypoglycemia over 6 months among older adults with type 1 diabetes (T1D) compared with blood glucose monitor...

Applications of artificial intelligence in prostate cancer histopathology.

Urologic oncology
The diagnosis of prostate cancer (PCa) depends on the evaluation of core needle biopsies by trained pathologists. Artificial intelligence (AI) derived models have been created to address the challenges posed by pathologists' increasing workload, work...

Application of artificial neural networks in reproductive medicine.

Human fertility (Cambridge, England)
With the emergence of the age of information, the data on reproductive medicine has improved immensely. Nonetheless, healthcare workers who wish to utilise the relevance and implied value of the various data available to aid clinical decision-making ...