Prescriptions

Integrating Artificial Intelligence and Bioinformatics Methods to Identify Disruptive STAT1 Variants Impacting Protein Stability and Function.

The Signal Transducer and Activator of Transcription 1 () gene is an essential component of the JAK-STAT signaling pathway. This pathway plays a pivotal role in the regulation of different cellular processes, including immune responses, cell growth, and apoptosis. Mutations in the gene contribute to a variety of immune system dysfunctions. We aim to identify disease-susceptible single-nucleotid...

Radiotherapy dose prediction using off-the-shelf segmentation networks: A feasibility study with GammaPod planning.

BACKGROUND: Radiotherapy requires precise, patient-specific treatment planning to achieve high-quality dose distributions that improve patient outcomes. Traditional manual planning is time-consuming and clinically impractical for performing necessary plan trade-off comparisons, including treatment modality selection, prescription dose settings, and organ at risk (OAR) constraints. A time-efficient...

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women.

Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditio...

The EU project Real4Reg: unlocking real-world data with AI.

BACKGROUND: The use of real-world data is established in post-authorization regulatory processes such as pharmacovigilance of drugs and medical device...

Large Model Era: Deep Learning in Osteoporosis Drug Discovery.

Osteoporosis is a systemic microstructural degradation of bone tissue, often accompanied by fractures, pain, and other complications, resulting in a d...

SynthMol: A Drug Safety Prediction Framework Integrating Graph Attention and Molecular Descriptors into Pre-Trained Geometric Models.

Drug safety is affected by multiple molecular properties and safety assessment is critical for clinical application. Evaluating a drug candidate's the...

Recent advances in AI-driven protein-ligand interaction predictions.

Structure-based drug discovery is a fundamental approach in modern drug development, leveraging computational models to predict protein-ligand interac...

A new era of psoriasis treatment: Drug repurposing through the lens of nanotechnology and machine learning.

Psoriasis is a persistent inflammatory skin disorder characterized by hyper-proliferation and abnormal epidermal differentiation. Conventional treatme...

Application of causal forests to randomised controlled trial data to identify heterogeneous treatment effects: a case study.

BACKGROUND: Classical approaches to subgroup analysis in randomised controlled trials (RCTs) to identify heterogeneous treatment effects (HTEs) involv...

Characterizing patients at higher cardiovascular risk for prescribed stimulants: Learning from health records data with predictive analytics and data mining techniques.

OBJECTIVE: Given the significantly increased number of individuals prescribed stimulants in the past decade, there has been growing concern regarding ...

Attention-augmented multi-domain cooperative graph representation learning for molecular interaction prediction.

Accurate identification of molecular interactions is crucial for biological network analysis, which can provide valuable insights into fundamental reg...

Advertising or adversarial? AdvSign: Artistic advertising sign camouflage for target physical attacking to object detector.

Deep learning models are often vulnerable to adversarial attacks in both digital and physical environments. Particularly challenging are physical atta...

Simulation of human-vehicle interaction at right-turn unsignalized intersections: A game-theoretic deep maximum entropy inverse reinforcement learning method.

The safety of pedestrians in urban transportation systems has emerged as a significant research topic. As a vulnerable group within this transportatio...

Utilizing machine learning for predicting drug release from polymeric drug delivery systems.

Polymeric drug delivery systems (PDDS) play a crucial role in controlled drug release, providing improved therapeutic outcomes. However, formulating P...

Hyperbolic multivariate feature learning in higher-order heterogeneous networks for drug-disease prediction.

New drug discovery has always been a costly, time-consuming process with a high failure rate. Repurposing existing drugs offers a valuable alternative...

Convolutional neural network for gesture recognition human-computer interaction system design.

Gesture interaction applications have garnered significant attention from researchers in the field of human-computer interaction due to their inherent...

Dose prediction via deep learning to enhance treatment planning of lung radiotherapy including simultaneous integrated boost techniques.

BACKGROUND: Recent studies have shown deep learning techniques are able to predict three-dimensional (3D) dose distributions of radiotherapy treatment...

Deep learning based coronary vessels segmentation in X-ray angiography using temporal information.

Invasive coronary angiography (ICA) is the gold standard imaging modality during cardiac interventions. Accurate segmentation of coronary vessels in I...

RNA-protein interaction prediction using network-guided deep learning.

Accurate computational determination of RNA-protein interactions remains challenging, particularly when encountering unknown RNAs and proteins. The li...

Artificial Intuition and accelerating the process of antimicrobial drug discovery.

New drug development is a very challenging, expensive, and usually time-consuming process. This issue is very important with regard to antimicrobials,...