FDA General

FormulationBCS: A Machine Learning Platform Based on Diverse Molecular Representations for Biopharmaceutical Classification System (BCS) Class Prediction.

The Biopharmaceutics Classification System (BCS) has facilitated biowaivers and played a significant role in enhancing drug regulation and development efficiency. However, the productivity of measuring the key discriminative properties of BCS, solubility and permeability, still requires improvement, limiting high-throughput applications of BCS, which is essential for evaluating drug candidate deve...

Chemoenzymatic Synthesis Planning Guided by Reaction Type Score.

Thanks to the growing interest in computer-aided synthesis planning (CASP), a wide variety of retrosynthesis and retrobiosynthesis tools have been developed in the past decades. However, synthesis planning tools for multistep chemoenzymatic reactions are still rare despite the widespread use of enzymatic reactions in chemical synthesis. Herein, we report a reaction type score (RTscore)-guided chem...

AI-enabled clinical decision support tools for mental healthcare: A product review.

The review seeks to promote transparency in the availability of regulated AI-enabled Clinical Decision Support Systems (AI-CDSS) for mental healthcare...

Heparin in sepsis: current clinical findings and possible mechanisms.

Sepsis is a clinical syndrome resulting from the interaction between coagulation, inflammation, immunity and other systems. Coagulation activation is ...

Predefined-Time Convergent Kinematic Control of Robotic Manipulators With Unknown Models Based on Hybrid Neural Dynamics and Human Behaviors.

This article proposes a model-free kinematic control method with predefined-time convergence for robotic manipulators with unknown models. The predefi...

Needle in a haystack: Harnessing AI in drug patent searches and prediction.

The classification codes granted by patent offices are useful instruments for simplifying the bewildering variety of patents in existence. They are si...

Hybrid CNN-GRU Model for Real-Time Blood Glucose Forecasting: Enhancing IoT-Based Diabetes Management with AI.

For people with diabetes, controlling blood glucose level (BGL) is a significant issue since the disease affects how the body metabolizes food, which ...

Translation as a Biosignature.

Life on Earth relies on mechanisms to store heritable information and translate this information into cellular machinery required for biological activ...

Accurate Spatial Heterogeneity Dissection and Gene Regulation Interpretation for Spatial Transcriptomics using Dual Graph Contrastive Learning.

Recent advances in spatial transcriptomics have enabled simultaneous preservation of high-throughput gene expression profiles and the spatial context,...

-targeted AI-driven vaccines: a paradigm shift in gastric cancer prevention.

, a globally prevalent pathogen Group I carcinogen, presents a formidable challenge in gastric cancer prevention due to its increasing antimicrobial r...

External validation and performance analysis of a deep learning-based model for the detection of intracranial hemorrhage.

PurposeWe aimed to investigate the external validation and performance of an FDA-approved deep learning model in labeling intracranial hemorrhage (ICH...

Regulating professional ethics in a context of technological change.

BACKGROUND: Technological change is impacting the work of health professionals, especially with recent developments in artificial intelligence. Resear...

Creating a standardized tool for the evaluation and comparison of artificial intelligence-based computer-aided detection programs in colonoscopy: a modified Delphi approach.

BACKGROUND AND AIMS: Multiple computer-aided detection (CADe) software programs have now achieved regulatory approval in the United States, Europe, an...

The translation of in-house imaging AI research into a medical device ensuring ethical and regulatory integrity.

This manuscript delineates the pathway from in-house research on Artificial Intelligence (AI) to the development of a medical device, addressing criti...

A Multicenter Evaluation of the Impact of Therapies on Deep Learning-Based Electrocardiographic Hypertrophic Cardiomyopathy Markers.

Artificial intelligence-enhanced electrocardiography (AI-ECG) can identify hypertrophic cardiomyopathy (HCM) on 12-lead ECGs and offers a novel way to...

Unsupervised Learning-Assisted Acoustic-Driven Nano-Lens Holography for the Ultrasensitive and Amplification-Free Detection of Viable Bacteria.

Bacterial infection is a crucial factor resulting in public health issues worldwide, often triggering epidemics and even fatalities. The accurate, rap...

Accurate non-invasive detection of MASH with fibrosis F2-F3 using a lightweight machine learning model with minimal clinical and metabolomic variables.

BACKGROUND: There are no known non-invasive tests (NITs) designed for accurately detecting metabolic dysfunction-associated steatohepatitis (MASH) wit...

Artificial intelligence-based drug repurposing with electronic health record clinical corroboration: A case for ketamine as a potential treatment for amphetamine-type stimulant use disorder.

BACKGROUND AND AIMS: Amphetamine-type stimulants are the second-most used illicit drugs globally, yet there are no US Food and Drug Administration (FD...

Analysis of solid-state NMR data facilitated by MagRO_NMRViewJ with Graph_Robot: Application for membrane protein and amyloid.

Solid-state NMR (ssNMR) methods have continued to be developed in recent years for the efficient assignment of signals and 3D structure modeling of bi...

Explainable machine learning models for predicting the acute toxicity of pesticides to sheepshead minnow (Cyprinodon variegatus).

A quantitative structure-activity relationship (QSAR) study was conducted on 313 pesticides to predict their acute toxicity to Sheepshead minnow (Cypr...