Prescriptions

Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data.

With the recent advances in deep learning, wearable sensors have increasingly been used in automated animal activity recognition. However, there are two major challenges in improving recognition performance-multi-modal feature fusion and imbalanced data modeling. In this study, to improve classification performance for equine activities while tackling these two challenges, we developed a cross-mod...

Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases.

In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms that resist conventional antibiotic treatment has steadily increased. Thus, it is now unquestionable that infectious diseases are significant global burdens that urgently require innovative treatment strategies. Emerging studies have demonstrated that artificial intelligence (AI) can transform drug deliver...

Hybrid COVID-19 segmentation and recognition framework (HMB-HCF) using deep learning and genetic algorithms.

COVID-19 (Coronavirus) went through a rapid escalation until it became a pandemic disease. The normal and manual medical infection discovery may take ...

Emergent antibacterial activity of -(thiazol-2-yl)benzenesulfonamides in conjunction with cell-penetrating octaarginine.

Hybrid antimicrobials that combine the effect of two or more agents represent a promising antibacterial therapeutic strategy. In this work, we have sy...

Dengue models based on machine learning techniques: A systematic literature review.

BACKGROUND: Dengue modeling is a research topic that has increased in recent years. Early prediction and decision-making are key factors to control de...

CBDPS 1.0: A Python GUI Application for Machine Learning Models to Predict Bitter-Tasting Children's Oral Medicines.

Bitter tastes are innately aversive and are thought to help protect animals from consuming poisons. Children are extremely sensitive to drug tastes, a...

AttentionDDI: Siamese attention-based deep learning method for drug-drug interaction predictions.

BACKGROUND: Drug-drug interactions (DDIs) refer to processes triggered by the administration of two or more drugs leading to side effects beyond those...

I, robot: depression plays different roles in human-human and human-robot interactions.

Socially engaging robots have been increasingly applied to alleviate depressive symptoms and to improve the quality of social life among different pop...

Effect of Patient Clinical Variables in Osteoporosis Classification Using Hip X-rays in Deep Learning Analysis.

: A few deep learning studies have reported that combining image features with patient variables enhanced identification accuracy compared with image-...

Generalized Deep Learning EEG Models for Cross-Participant and Cross-Task Detection of the Vigilance Decrement in Sustained Attention Tasks.

Tasks which require sustained attention over a lengthy period of time have been a focal point of cognitive fatigue research for decades, with these ta...

Personalized Exercise Programs Based upon Remote Assessment of Motor Fitness: A Pilot Study among Healthy People Aged 65 Years and Older.

BACKGROUND: The World Health Organization has recently updated exercise guidelines for people aged >65 years, emphasizing the inclusion of multiple fi...

Chromatin interaction neural network (ChINN): a machine learning-based method for predicting chromatin interactions from DNA sequences.

Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is limi...

An interpretable machine learning method for homo-trimeric protein interface residue-residue interaction prediction.

Protein-protein interaction plays an important role in life activities. A more fine-grained analysis, such as residues and atoms level, will better be...

A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD.

Inflammatory bowel diseases (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC) are chronic inflammation within the gastrointestinal tract....

Human activity recognition using wearable sensors, discriminant analysis, and long short-term memory-based neural structured learning.

Healthcare using body sensor data has been getting huge research attentions by a wide range of researchers because of its good practical applications ...

Mammographic Surveillance After Breast-Conserving Therapy: Impact of Digital Breast Tomosynthesis and Artificial Intelligence-Based Computer-Aided Detection.

Postoperative mammograms present interpretive challenges due to postoperative distortion and hematomas. The application of digital breast tomosyn-the...

Fast and Accurate Ophthalmic Medication Bottle Identification Using Deep Learning on a Smartphone Device.

PURPOSE: To assess the accuracy and efficacy of deep learning models, specifically convolutional neural networks (CNNs), to identify glaucoma medicati...

A case of fatal multidrug intoxication involving flualprazolam: distribution in body fluids and solid tissues.

PURPOSE: Designer benzodiazepines (DBZDs) increasingly emerged on the novel psychoactive substance (NPS) market in the last few years. They are usuall...

Vehicle Trajectory Prediction Using Hierarchical Graph Neural Network for Considering Interaction among Multimodal Maneuvers.

Predicting the trajectories of surrounding vehicles by considering their interactions is an essential ability for the functioning of autonomous vehicl...

A Convolutional Neural Network System to Discriminate Drug-Target Interactions.

Biological targets are most commonly proteins such as enzymes, ion channels, and receptors. They are anything within a living organism to bind with so...