Alternative Medicine

Explaining One-Dimensional Convolutional Models in Human Activity Recognition and Biometric Identification Tasks.

Due to wearables' popularity, human activity recognition (HAR) plays a significant role in people's routines. Many deep learning (DL) approaches have studied HAR to classify human activities. Previous studies employ two HAR validation approaches: subject-dependent (SD) and subject-independent (SI). Using accelerometer data, this paper shows how to generate visual explanations about the trained mod...

Electrocardiogram analysis of post-stroke elderly people using one-dimensional convolutional neural network model with gradient-weighted class activation mapping.

Stroke is the second leading cause of death globally after ischemic heart disease, also a risk factor of cardioembolic stroke. Thus, we postulate that heartbeats encapsulate vital signals related to stroke. With the rapid advancement of deep neural networks (DNNs), it emerges as a powerful tool to decipher intriguing heartbeat patterns associated with post-stroke patients. In this study, we propos...

CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation.

BACKGROUND: The morbidity of pulmonary embolism (PE) is only lower than that of coronary heart disease and hypertension. Early detection, early diagno...

Structure of cytoplasmic ring of nuclear pore complex by integrative cryo-EM and AlphaFold.

INTRODUCTION The nuclear pore complex (NPC) is the molecular conduit in the nuclear membrane of eukaryotic cells that regulates import and export of b...

Intracerebral hemorrhage detection on computed tomography images using a residual neural network.

Intracerebral hemorrhage (ICH) is a high mortality rate, critical medical injury, produced by the rupture of a blood vessel of the vascular system ins...

HDI Highlighter, The First Intelligent Tool to Screen the Literature on Herb-Drug Interactions.

Herbal food supplements are commonly used and can be an important part of patient self-care. Like all other bio-active and therapeutic products, they ...

In silico prediction of potential drug-induced nephrotoxicity with machine learning methods.

In recent years, drug-induced nephrotoxicity has been one of the main reasons for the failure of drug development. Early prediction of the nephrotoxic...

Context-Aware Multi-Scale Aggregation Network for Congested Crowd Counting.

In this paper, we propose a context-aware multi-scale aggregation network named CMSNet for dense crowd counting, which effectively uses contextual inf...

DeepBtoD: Improved RNA-binding proteins prediction via integrated deep learning.

RNA-binding proteins (RBPs) have crucial roles in various cellular processes such as alternative splicing and gene regulation. Therefore, the analysis...

One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data.

Integrative analysis of large-scale single-cell RNA sequencing (scRNA-seq) datasets can aggregate complementary biological information from different ...

A Single Model Deep Learning Approach for Alzheimer's Disease Diagnosis.

Early and accurate diagnosis of Alzheimer's disease (AD) and its prodromal period mild cognitive impairment (MCI) is essential for the delayed disease...

The Future Ethics of Artificial Intelligence in Medicine: Making Sense of Collaborative Models.

This article examines the role of medical doctors, AI designers, and other stakeholders in making applied AI and machine learning ethically acceptable...

Artificial intelligence in veterinary medicine.

Artificial intelligence (AI) is a branch of computer science in which computer systems are designed to perform tasks that mimic human intelligence. To...

A visually interpretable detection method combines 3-D ECG with a multi-VGG neural network for myocardial infarction identification.

BACKGROUND AND OBJECTIVE: The automatic recognition of myocardial infarction (MI) by artificial intelligence (AI) has been an emerging topic of academ...

Multitask deep learning with dynamic task balancing for quantum mechanical properties prediction.

Predicting quantum mechanical properties (QMPs) is very important for the innovation of material and chemistry science. Multitask deep learning models...

Artificial intelligence enabled automated diagnosis and grading of ulcerative colitis endoscopy images.

Endoscopic evaluation to reliably grade disease activity, detect complications including cancer and verification of mucosal healing are paramount in t...

Publishing fast and slow: A path toward generalizability in psychology and AI.

Artificial intelligence (AI) shares many generalizability challenges with psychology. But the fields publish differently. AI publishes fast, through r...

Research Note: Study on the antibacterial activity of Chinese herbal medicine against Aspergillus flavus and Aspergillus fumigatus of duck origin in laying hens.

Aspergillus flavus and Aspergillus fumigatus were derived and identified from the ducks infected with fungi. In order to investigate the effectiveness...

ICEO, a biological ontology for representing and analyzing bacterial integrative and conjugative elements.

Bacterial integrative and conjugative elements (ICEs) are highly modular mobile genetic elements critical to the horizontal transfer of antibiotic res...

Classification of rotator cuff tears in ultrasound images using deep learning models.

Rotator cuff tears (RCTs) are one of the most common shoulder injuries, which are typically diagnosed using relatively expensive and time-consuming di...