Prescriptions

Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.

Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergence of viral diseases is expected to accelerate; these data indicate the need for a proactive approach to develop widely active family specific and cross family therapies for future disease outbreaks. Viral disease such as pneumonia, severe acute respi...

Generalisation Gap of Keyword Spotters in a Cross-Speaker Low-Resource Scenario.

Models for keyword spotting in continuous recordings can significantly improve the experience of navigating vast libraries of audio recordings. In this paper, we describe the development of such a keyword spotting system detecting regions of interest in Polish call centre conversations. Unfortunately, in spite of recent advancements in automatic speech recognition systems, human-level transcriptio...

From Drug Molecules to Thermoset Shape Memory Polymers: A Machine Learning Approach.

Ultraviolet (UV)-curable thermoset shape memory polymers (TSMPs) with high recovery stress but mild glass transition temperature () are highly desired...

NegStacking: Drug-Target Interaction Prediction Based on Ensemble Learning and Logistic Regression.

Drug-target interactions (DTIs) identification is an important issue of drug research, and many methods proposed to predict potential DTIs based on ma...

Prediction of Drug-Target Interactions Based on Network Representation Learning and Ensemble Learning.

Identifying interactions between drugs and target proteins is a critical step in the drug development process, as it helps identify new targets for dr...

Waymarking in Social Robots: Environment Signaling Using Human-Robot Interaction.

Travellers use the term waymarking to define the action of posting signs, or waymarks, along a route. These marks are intended to be points of referen...

User-Interactive Robot Skin With Large-Area Scalability for Safer and Natural Human-Robot Collaboration in Future Telehealthcare.

With the fourth revolution of healthcare, i.e., Healthcare 4.0, collaborative robotics is spilling out from traditional manufacturing and will blend i...

A contextual multi-task neural approach to medication and adverse events identification from clinical text.

Effective wide-scale pharmacovigilance calls for accurate named entity recognition (NER) of medication entities such as drugs, dosages, reasons, and a...

Process performance of a new liquid medication dispensing robot.

OBJECTIVES: Liquid medications provide an alternative to splitting pills and dosages by measuring an amount of liquid rather than crushing tablets or ...

Increasing efficiency and accuracy of magnetic interaction calculations in colloidal simulation through machine learning.

Calculating the magnetic interaction between magnetic particles that are positioned in close proximity to one another is a surprisingly challenging ta...

Machine Learning Approaches in Traditional Chinese Medicine: A Systematic Review.

Machine learning (ML), as a branch of artificial intelligence, acquires the potential and meaningful rules from the mass of data via diverse algorithm...

A machine learning pipeline revealing heterogeneous responses to drug perturbations on vascular smooth muscle cell spheroid morphology and formation.

Machine learning approaches have shown great promise in biology and medicine discovering hidden information to further understand complex biological a...

Untethered Microrobots for Active Drug Delivery: From Rational Design to Clinical Settings.

Recent advances of untethered microrobots, which navigate the complex regions in vivo for therapeutics, have presented promising multiple applications...

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach.

Medical distrust is a potent barrier to participation in HIV care and medication use among African American/Black and Latino (AABL) persons living wit...

Picture-word order compound protein interaction: Predicting compound-protein interaction using structural images of compounds.

Identifying potential associations between proteins and compounds is significant and challenging in the drug discovery process. Existing deep-learning...

A Shrewd Artificial Neural Network-Based Hybrid Model for Pervasive Stress Detection of Students Using Galvanic Skin Response and Electrocardiogram Signals.

Mental illness issues are a very common health issue in youths and adults across the world. The usage of real-time data analytics in health care has a...

Drug repurposing for COVID-19 using graph neural network and harmonizing multiple evidence.

Since the 2019 novel coronavirus disease (COVID-19) outbreak in 2019 and the pandemic continues for more than one year, a vast amount of drug research...

Assessment of the Cytotoxic Activity of Alcoholic Extract of on Breast Cancer Cell Line.

The spread of different types of cancer has been on a rise in the recent century. The use of chemical medications develops drug resistance and causes ...

Ultrasound Elastography under Deep Learning Algorithm to Analyze the Therapeutic Effect of Clustered Regularly Interspaced Short Palindromic Repeats Short Hairpin Ribonucleic Acid Nanoparticles on Cervical Cancer.

This study aimed to analyze the effect of the deep learning algorithm on ultrasound elastography on the treatment of cervical cancer with clustered re...

Design and Characterization of Liposomal Methotrexate and Its Effect on BT-474 Breast Cancer Cell Line.

Breast cancer is the most common type of cancer among women worldwide. Traditional treatments, including chemotherapy, surgery, mastectomy, and radio...