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Effect of multimodal diagnostic approach using deep learning-based automated detection algorithm for active pulmonary tuberculosis.

In this study, we developed a model to predict culture test results for pulmonary tuberculosis (PTB)...

Artificial intelligence and machine learning for clinical pharmacology.

Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug disco...

Revolutionizing Peptide-Based Drug Discovery: Advances in the Post-AlphaFold Era.

Peptide-based drugs offer high specificity, potency, and selectivity. However, their inherent flexib...

ChatRx: ChatGPT's potential to educate patients on medication adverse effects.

Evaluating Use of Artificial Intelligence for Drug Exposure and Effect Prediction.

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU.

Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and...

Current Trends and Challenges in Drug-Likeness Prediction: Are They Generalizable and Interpretable?

: Drug-likeness of a compound is an overall assessment of its potential to succeed in clinical trial...

An algorithm for drug discovery based on deep learning with an example of developing a drug for the treatment of lung cancer.

In this study, we present an algorithmic framework integrated within the created software platform t...

A simplified similarity-based approach for drug-drug interaction prediction.

Drug-drug interactions (DDIs) are a critical component of drug safety surveillance. Laboratory studi...

Validation of a Natural Language Machine Learning Model for Safety Literature Surveillance.

INTRODUCTION: As part of routine safety surveillance, thousands of articles of potential interest ar...

Deep Generative Models in Drug Molecule Generation.

The discovery of new drugs has important implications for human health. Traditional methods for drug...

Calibrated geometric deep learning improves kinase-drug binding predictions.

Protein kinases regulate various cellular functions and hold significant pharmacological promise in ...

Generation of focused drug molecule library using recurrent neural network.

CONTEXT: With the wide application of deep learning in drug research and development, de novo molecu...

Artificial intelligence: Machine learning approach for screening large database and drug discovery.

Recent research in drug discovery dealing with many faces difficulties, including development of new...

Deep learning-enabled natural language processing to identify directional pharmacokinetic drug-drug interactions.

BACKGROUND: During drug development, it is essential to gather information about the change of clini...

Effect of SARS-CoV-2 spike protein exposure on ACE2 and interleukin 6 productions in human adipocytes: An in-vitro study.

Since adipocytes play a crucial role in pathogenesis of severe acute respiratory syndrome coronaviru...

Developing and scaling up captopril-loaded electrospun ethyl cellulose fibers for sustained-release floating drug delivery.

In this work ethyl cellulose (EC) was used as the matrix polymer and loaded with captopril, with the...

The preliminary in vitro study and application of deep learning algorithm in cone beam computed tomography image implant recognition.

To properly repair and maintain implants, which are bone tissue implants that replace natural tooth ...

Advanced deep learning techniques for early disease prediction in cauliflower plants.

Agriculture plays a pivotal role in the economies of developing countries by providing livelihoods, ...

Efficacy and Safety of Chinese Herbal Medicine in Patients with Acute Intracerebral Hemorrhage: Protocol for a Randomized Placebo-Controlled Double-Blinded Multicenter Trial.

INTRODUCTION: The popular traditional Chinese medicine (TCM) compound FYTF-919 (Zhong Feng Xing Nao ...

Heterogeneous context interaction network for vehicle re-identification.

Capturing global and subtle discriminative information using attention mechanisms is essential to ad...