AIMC Topic: Humans

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Light-Fueled Polymer Film Capable of Directional Crawling, Friction-Controlled Climbing, and Self-Sustained Motion on a Human Hair.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Recent efforts in stimuli-responsive soft materials have enabled wirelessly controlled actuation with increasing degrees of freedom, yielding miniature robots capable of various locomotion in open environments such as on a plane or inside fluids. How...

Learning-based synthetic dual energy CT imaging from single energy CT for stopping power ratio calculation in proton radiation therapy.

The British journal of radiology
OBJECTIVE: Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR) map with a higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. This work presents a learning-based...

A systematic review of sutureless vascular anastomosis technologies.

Seminars in vascular surgery
Vascular anastomoses typically involve a handsewn technique requiring significant surgical training, expertise, and time. The aim of our systematic review was to identify and describe sutureless vascular anastomosis techniques. We performed a systema...

Novelelectronic health records applied for prediction of pre-eclampsia: Machine-learning algorithms.

Pregnancy hypertension
OBJECTIVE: To predict risk of pre-eclampsia (PE) in women using machine learning (ML) algorithms, based on electronic health records (EHR) collected at the early second trimester.

Predictive value of a novel Asian lung cancer screening nomogram based on artificial intelligence and epidemiological characteristics.

Thoracic cancer
BACKGROUND: To develop and validate a risk prediction nomogram based on a deep learning convolutional neural networks (CNN) model and epidemiological characteristics for lung cancer screening in patients with small pulmonary nodules (SPN).

A deep learning- and CT image-based prognostic model for the prediction of survival in non-small cell lung cancer.

Medical physics
OBJECTIVE: To assist clinicians in arranging personalized treatment, planning follow-up programs and extending survival times for non-small cell lung cancer (NSCLC) patients, a method of deep learning combined with computed tomography (CT) imaging fo...

DeepLC can predict retention times for peptides that carry as-yet unseen modifications.

Nature methods
The inclusion of peptide retention time prediction promises to remove peptide identification ambiguity in complex liquid chromatography-mass spectrometry identification workflows. However, due to the way peptides are encoded in current prediction mod...

Effect of Oxidized LDL on Platelet Shape, Spreading, and Migration Investigated with Deep Learning Platelet Morphometry.

Cells
Platelets are functionally versatile blood cells involved in thrombosis, hemostasis, atherosclerosis, and immune response. Platelet interaction with the immediate microenvironment in blood, vasculature, and tissues alters platelet morphology. The qua...

Role of Deep Learning in Predicting Aging-Related Diseases: A Scoping Review.

Cells
Aging refers to progressive physiological changes in a cell, an organ, or the whole body of an individual, over time. Aging-related diseases are highly prevalent and could impact an individual's physical health. Recently, artificial intelligence (AI)...