Prescriptions

Deep Learning Algorithm Based on Molecular Fingerprint for Prediction of Drug-Induced Liver Injury.

Drug-induced liver injury (DILI) is one the rare adverse drug reaction (ADR) and multifactorial endpoints. Current preclinical animal models struggle to anticipate it, and in silico methods have emerged as a way with significant potential for doing so. In this study, a high-quality dataset of 1573 compounds was assembled. The 48 classification models, which depended on six different molecular fing...

Perceptions on artificial intelligence-based decision-making for coexisting multiple long-term health conditions: protocol for a qualitative study with patients and healthcare professionals.

INTRODUCTION: Coexisting multiple health conditions is common among older people, a population that is increasing globally. The potential for polypharmacy, adverse events, drug interactions and development of additional health conditions complicates prescribing decisions for these patients. Artificial intelligence (AI)-generated decision-making tools may help guide clinical decisions in the contex...

CCL-DTI: contributing the contrastive loss in drug-target interaction prediction.

BACKGROUND: The Drug-Target Interaction (DTI) prediction uses a drug molecule and a protein sequence as inputs to predict the binding affinity value. ...

ConTIG: Continuous representation learning on temporal interaction graphs.

Representation learning on temporal interaction graphs (TIG) aims to model complex networks with the dynamic evolution of interactions on a wide range...

MFD-GDrug: multimodal feature fusion-based deep learning for GPCR-drug interaction prediction.

The accurate identification of drug-protein interactions (DPIs) is crucial in drug development, especially concerning G protein-coupled receptors (GPC...

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks.

For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatme...

Noninvasive Assessment of Kidney Injury by Combining Structure and Function Using Artificial Intelligence-Based Manganese-Enhanced Magnetic Resonance Imaging.

Contrast-enhanced magnetic resonance imaging (MRI) is seriously limited in kidney injury detection due to the nephrotoxicity of clinically used gadoli...

Prescription trend and lactic acidosis in patients prescribed metformin before and after the revision of package insert for allowing metformin administration to patients with moderately decreased kidney function based on real-world data from MID-NET in Japan.

INTRODUCTION: This study was conducted to understand the impact of package insert (PI) revision in Japan on 18 June 2019 to allow metformin use for pa...

SSF-DDI: a deep learning method utilizing drug sequence and substructure features for drug-drug interaction prediction.

BACKGROUND: Drug-drug interactions (DDI) are prevalent in combination therapy, necessitating the importance of identifying and predicting potential DD...

An integrated passive acoustic monitoring and deep learning pipeline for black-and-white ruffed lemurs (Varecia variegata) in Ranomafana National Park, Madagascar.

The urgent need for effective wildlife monitoring solutions in the face of global biodiversity loss has resulted in the emergence of conservation tech...

IUPHAR Review: New strategies for medications to treat substance use disorders.

Substance use disorders (SUDs) and drug overdose are a public health emergency and safe and effective treatments are urgently needed. Developing new m...

A magnetic multi-layer soft robot for on-demand targeted adhesion.

Magnetic soft robots have shown great potential for biomedical applications due to their high shape reconfigurability, motion agility, and multi-funct...

NeuroAIreh@b: an artificial intelligence-based methodology for personalized and adaptive neurorehabilitation.

Cognitive impairments are a prevalent consequence of acquired brain injury, dementia, and age-related cognitive decline, hampering individuals' daily ...

SSLDTI: A novel method for drug-target interaction prediction based on self-supervised learning.

Many computational methods have been proposed to identify potential drug-target interactions (DTIs) to expedite drug development. Graph neural network...

Mechanically Robust and Linearly Sensitive Soft Piezoresistive Pressure Sensor for a Wearable Human-Robot Interaction System.

Soft piezoresistive pressure sensors play an underpinning role in enabling a plethora of future Internet of Things (IoT) applications such as human-ro...

Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects.

Combination therapy has gained popularity in cancer treatment as it enhances the treatment efficacy and overcomes drug resistance. Although machine le...

Analyzing the influential factors of process safety culture by hybrid hidden content analysis and fuzzy DEMATEL.

Due to the complex nature of safety culture and process industries, several factors influence process safety culture. This paper presents a novel fram...

Wearable Sensors Assess the Effects of Human-Robot Collaboration in Simulated Pollination.

Pollination for indoor agriculture is hampered by environmental conditions, requiring farmers to pollinate manually. This increases the musculoskeleta...

PeNet: A feature excitation learning approach to advertisement click-through rate prediction.

Since the physical meaning of the fields of the dataset is unknown, we have to use the feature interaction method to select the correlated features an...

Effectiveness of continuity of care after robot-assisted laparoscopic adrenalectomy under ambulatory mode: a single-center intervention study.

To investigate the effectiveness of continuity of care after robot-assisted adrenal tumor resection under ambulatory mode. Patients who underwent robo...