AIMC Topic: Humans

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Bringing Structural Implications and Deep Learning-Based Drug Identification for Mutants.

Journal of chemical information and modeling
Colorectal cancer is considered one of the leading causes of death that is linked with the Kirsten Rat Sarcoma () harboring codons 13 and 61 mutations. The objective for this study is to search for clinically important codon 61 mutations and analyze ...

Trade-off Predictivity and Explainability for Machine-Learning Powered Predictive Toxicology: An in-Depth Investigation with Tox21 Data Sets.

Chemical research in toxicology
Selecting a model in predictive toxicology often involves a trade-off between prediction performance and explainability: should we sacrifice the model performance to gain explainability or vice versa. Here we present a comprehensive study to assess a...

Janus-like Jagged Structure with Nanocrystals for Self-Sorting Wearable Tactile Sensor.

ACS applied materials & interfaces
In this study, a self-sorting sensor was developed with the ability to distinguish between different pressure regimes and translate the pressure to electrical signals. Specifically, the self-sorting sensor can distinguish between soft and hard pressu...

A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and progression detection have been intensively studied. Nevertheless, research studies often have little effect on clinical practice mainly due to the following reasons: (1)...

Verifying explainability of a deep learning tissue classifier trained on RNA-seq data.

Scientific reports
For complex machine learning (ML) algorithms to gain widespread acceptance in decision making, we must be able to identify the features driving the predictions. Explainability models allow transparency of ML algorithms, however their reliability with...

Head motion classification using thread-based sensor and machine learning algorithm.

Scientific reports
Human machine interfaces that can track head motion will result in advances in physical rehabilitation, improved augmented reality/virtual reality systems, and aid in the study of human behavior. This paper presents a head position monitoring and cla...

Deep convolutional neural networks to predict cardiovascular risk from computed tomography.

Nature communications
Coronary artery calcium is an accurate predictor of cardiovascular events. While it is visible on all computed tomography (CT) scans of the chest, this information is not routinely quantified as it requires expertise, time, and specialized equipment....

Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare.

Nature communications
Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis, which is critical in reducing mortality, is challenging as many of its signs and symptoms are similar to other less critical conditions. We develop an artifici...

Effects of wearable ankle robotics for stair and over-ground training on sub-acute stroke: a randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: Wearable ankle robotics could potentially facilitate intensive repetitive task-specific gait training on stair environment for stroke rehabilitation. A lightweight (0.5 kg) and portable exoskeleton ankle robot was designed to facilitate o...