Medicolegal

Novel machine learning approaches revolutionize protein knowledge.

Breakthrough methods in machine learning (ML), protein structure prediction, and novel ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models of proteins and annotating their functions on a large scale is no longer limited by time and resources. The most recent method to be top ranked by the Critical Assessment of Structure Prediction (CASP) assessment, Alp...

Exploring Machine Learning-Based Fault Monitoring for Polymer-Based Additive Manufacturing: Challenges and Opportunities.

Three-dimensional printing, often known as additive manufacturing (AM), is a groundbreaking technique that enables rapid prototyping. Monitoring AM delivers benefits, as monitoring print quality can prevent waste and excess material costs. Machine learning is often applied to automating fault detection processes, especially in AM. This paper explores recent research on machine learning-based mecha...

Using deep-learning predictions of inter-residue distances for model validation.

Determination of protein structures typically entails building a model that satisfies the collected experimental observations and its deposition in th...

Assessing visualization in robotic-assisted surgery: demystifying a misty lens.

Despite major technological advancements in robotic-assisted laparoscopic surgery (RAS), there remain shortcomings yet to be addressed. This study ass...

Electrospray mode discrimination with current signal using deep convolutional neural network and class activation map.

The electrospray process has been extensively applied in various fields, including energy, display, sensor, and biomedical engineering owing to its ab...

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HD...

Explainable, trustworthy, and ethical machine learning for healthcare: A survey.

With the advent of machine learning (ML) and deep learning (DL) empowered applications for critical applications like healthcare, the questions about ...

Accident Liability Determination of Autonomous Driving Systems Based on Artificial Intelligence Technology and Its Impact on Public Mental Health.

With the rise of self-driving technology research, the establishment of a scientific and perfect legal restraint and supervision system for self-drivi...

Deep-learning prediction of amyloid deposition from early-phase amyloid positron emission tomography imaging.

OBJECTIVE: While the use of biomarkers for the detection of early and preclinical Alzheimer's Disease has become essential, the need to wait for over ...

Controlled Growth of Wafer-Scale Transition Metal Dichalcogenides with a Vertical Composition Gradient for Artificial Synapses with High Linearity.

Artificial synapses are promising for dealing with large amounts of data computing. Great progress has been made recently in terms of improving the on...

Close-range remote sensing-based detection and identification of macroplastics on water assisted by artificial intelligence: A review.

Detection and identification of macroplastic debris in aquatic environments is crucial to understand and counter the growing emergence and current dev...

The immuneoreaction and antioxidant status of Chinese mitten crab (Eriocheir sinensis) involve protein metabolism and the response of mTOR signaling pathway to dietary methionine levels.

To study the effects of dietary methionine on growth performance, immunity, antioxidant capacity, protein metabolism, inflammatory response and apopto...

Machine Learning-Enabled Prediction of 3D-Printed Microneedle Features.

Microneedles (MNs) introduced a novel injection alternative to conventional needles, offering a decreased administration pain and phobia along with mo...

Collaborative Robotic Wire + Arc Additive Manufacture and Sensor-Enabled In-Process Ultrasonic Non-Destructive Evaluation.

The demand for cost-efficient manufacturing of complex metal components has driven research for metal Additive Manufacturing (AM) such as Wire + Arc A...

Deep learning-based 3D MRI contrast-enhanced synthesis from a 2D noncontrast T2Flair sequence.

PURPOSE: Gadolinium-based contrast agents (GBCAs) have been successfully applied in magnetic resonance (MR) imaging to facilitate better lesion visual...

Deep learning modeling mA deposition reveals the importance of downstream cis-element sequences.

The N-methyladenosine (mA) modification is deposited to nascent transcripts on chromatin, but its site-specificity mechanism is mostly unknown. Here w...

Toward automatic beam angle selection for pencil-beam scanning proton liver treatments: A deep learning-based approach.

BACKGROUND: Dose deposition characteristics of proton radiation can be advantageous over photons. Proton treatment planning, however, poses additional...

Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System.

Blockchain is a recent revolutionary technology primarily associated with cryptocurrencies. It has many unique features including its acting as a dece...

Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method.

White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the immune system. They are also known as "defender cells." B...

Calculation of volume fractions regardless scale deposition in the oil industry pipelines using feed-forward multilayer perceptron artificial neural network and MCNP6 code.

During the production of oil and gas, barium sulfate (BaSO) scale occurs on the inner walls of the tubes leading the reduction of the internal diamete...