Results 41 to 50 of about 709,328 (257)

A machine learning framework for predicting drug–drug interactions

Scientific Reports, 2021
Understanding drug–drug interactions is an essential step to reduce the risk of adverse drug events before clinical drug co-prescription. Existing methods, commonly integrating heterogeneous data to increase model performance, often suffer from a high ...
Suyu Mei, Kun Zhang
doaj   +1 more source

Ironic Medications: A Narrative‐Based Psycho‐Educational Intervention to Explore Patient–Provider Communication in Adolescents With Haematological Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Adolescents with haematological malignancies face significant emotional and relational challenges, often accompanied by difficulties in communicating their needs within the healthcare context. To address these issues, a narrative‐based psycho‐educational intervention based on the creation and prescription of Ironic Medications was ...
Marta Stoppa, Elena Pagani Bagliacca, Selena Russo, Giulia Rampoldi, Maria Grazia Strepparava, Adriana Cristina Balduzzi, Andrea Biondi, Marco Spinelli   +7 more
wiley   +1 more source

AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders

BMC Bioinformatics, 2021
Background Drug–target interaction (DTI) plays a vital role in drug discovery. Identifying drug–target interactions related to wet-lab experiments are costly, laborious, and time-consuming.
Seyedeh Zahra Sajadi, Mohammad Ali Zare Chahooki, Sajjad Gharaghani, Karim Abbasi   +3 more
doaj   +1 more source

Effective drug–target interaction prediction with mutual interaction neural network

Bioinformatics, 2022
AbstractMotivationAccurately predicting drug–target interaction (DTI) is a crucial step to drug discovery. Recently, deep learning techniques have been widely used for DTI prediction and achieved significant performance improvement. One challenge in building deep learning models for DTI prediction is how to appropriately represent drugs and targets ...
Fei Li, Ziqiao Zhang, Jihong Guan, Shuigeng Zhou   +3 more
openaire   +2 more sources

BMT4me En Español: Multisite Feasibility and Usability Testing of a Spanish‐Language mHealth Adherence Support App for Spanish‐Speaking Caregivers of Children After Hematopoietic Stem Cell Transplantation and Cancer Treatment

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Medication nonadherence during the first 100 days after pediatric hematopoietic stem cell transplantation (HSCT) and during oncology treatment increases risk for complications. BMT4me is a caregiver‐facing mobile health (mHealth) application providing medication reminders, symptom tracking, and note‐taking features to support ...
Micah A. Skeens, Madeline R. Peek, Bianca Franklin, Emre Sezgin, Melissa Beauchemin   +4 more
wiley   +1 more source

Drug repurposing and prediction of multiple interaction types via graph embedding

BMC Bioinformatics, 2023
Background Finding drugs that can interact with a specific target to induce a desired therapeutic outcome is key deliverable in drug discovery for targeted treatment.
E. Amiri Souri, A. Chenoweth, S. N. Karagiannis, S. Tsoka   +3 more
doaj   +1 more source

Identifying potential drug-target interactions based on ensemble deep learning

Frontiers in Aging Neuroscience, 2023
IntroductionDrug-target interaction prediction is one important step in drug research and development. Experimental methods are time consuming and laborious.MethodsIn this study, we developed a novel DTI prediction method called EnGDD by combining ...
Liqian Zhou, Yuzhuang Wang, Lihong Peng, Zejun Li, Xueming Luo   +4 more
doaj   +1 more source

Drug Target Interaction Prediction

International Journal of Advanced Research in Science, Communication and Technology
Drug–target interaction (DTI) prediction is vital to drug discovery, assisting in the identification of drug- target protein interactions more efficiently than usual methods of experimentation, which are frequently costly and time-consuming. To In order to tackle these issues, this piece presents a web-based application that predicts DTIs and ...
null Ruby Sheikh, null Dr. Soumyasri S M
openaire   +1 more source

Misperception of Body Weight After Childhood Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Misperception of body weight can negatively impact the weight management efforts of childhood cancer survivors (CCSs). Both being overweight or underweight are associated with chronic health conditions commonly observed in CCS; therefore, accurate weight perception is critical for reducing long‐term health risks.
Fabiën N. Belle, Tomáš Sláma, Eva Haegler‐Laube, Reto D. Kurmann, Gabriela M. Kuster, Christoph Saner, Eva Scheler, Yara Shoman, Christina Schindera   +8 more
wiley   +1 more source

EmbedDTI: Enhancing the Molecular Representations via Sequence Embedding and Graph Convolutional Network for the Prediction of Drug-Target Interaction

Biomolecules, 2021
The identification of drug-target interaction (DTI) plays a key role in drug discovery and development. Benefitting from large-scale drug databases and verified DTI relationships, a lot of machine-learning methods have been developed to predict DTIs ...
Yuan Jin, Jiarui Lu, Runhan Shi, Yang Yang   +3 more
doaj   +1 more source