FDA General

SpikeDeep-classifier: a deep-learning based fully automatic offline spike sorting algorithm.

Advancements in electrode design have resulted in micro-electrode arrays with hundreds of channels for single cell recordings. In the resulting electrophysiological recordings, each implanted electrode can record spike activity (SA) of one or more neurons along with background activity (BA). The aim of this study is to isolate SA of each neural source. This process is called spike sorting or spike...

Precision Regulation Approach: A COVID-19 Triggered Regulatory Drive in South Korea.

COVID-19 has triggered various changes in our everyday lives and how we conceptualize the functions of governments. Some areas require stricter forms of regulation while others call for deregulation. The challenge for the regulatory authorities is to manage these potentially conflicting demands in regulation and define coherently their overall regulatory rationale. The precision regulation approac...

Mediating artificial intelligence developments through negative and positive incentives.

The field of Artificial Intelligence (AI) is going through a period of great expectations, introducing a certain level of anxiety in research, busines...

Prediction of adverse drug reactions using drug convolutional neural networks.

Prediction of Adverse Drug Reactions (ADRs) has been an important aspect of Pharmacovigilance because of its impact in the pharma industry. The standa...

Mechanics and Morphological Compensation Strategy for Trimmed Soft Whisker Sensor.

Recent studies have been inspired by natural whiskers for a proposal of tactile sensing system to augment the sensory ability of autonomous robots. In...

Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis.

There has been a surge of interest in artificial intelligence and machine learning (AI/ML)-based medical devices. However, it is poorly understood how...

Simultaneous spectrophotometric quantitative analysis of velpatasvir and sofosbuvir in recently approved FDA pharmaceutical preparation using artificial neural networks and genetic algorithm artificial neural networks.

Two chemometric assisted spectrophotometric models were applied for the quantitative analysis of velpatasvir and sofosbuvir in their newly FDA approve...

Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method.

BACKGROUND : Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. ...

Branching principles of animal and plant networks identified by combining extensive data, machine learning and modelling.

Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi and animal...

A machine learning approach to modeling PTSD and difficulties in emotion regulation.

Despite evidence for the association between emotion regulation difficulties and posttraumatic stress disorder (PTSD), less is known about the specifi...

iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network.

A promoter is a short DNA sequence near to the start codon, responsible for initiating transcription of a specific gene in genome. The accurate recogn...

Robotic assistance for quick and accurate image-guided needle placement.

Computed tomography (CT) image-guided procedures including biopsy, drug delivery, and ablation are gaining increasing application in medicine. Robotic...

Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.

In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets a...

Applications of artificial intelligence in drug development using real-world data.

The US Food and Drug Administration (FDA) has been actively promoting the use of real-world data (RWD) in drug development. RWD can generate important...

Repurposing potential of FDA-approved and investigational drugs for COVID-19 targeting SARS-CoV-2 spike and main protease and validation by machine learning algorithm.

The present study aimed to assess the repurposing potential of existing antiviral drug candidates (FDA-approved and investigational) against SARS-CoV-...

Assessing Drug Development Risk Using Big Data and Machine Learning.

Identifying new drug targets and developing safe and effective drugs is both challenging and risky. Furthermore, characterizing drug development risk,...

Artificial intelligence and its impact on quality improvement in upper and lower gastrointestinal endoscopy.

Artificial intelligence (AI) and its application in medicine has grown large interest. Within gastrointestinal (GI) endoscopy, the field of colonoscop...

Deep neural networks for inferring binding sites of RNA-binding proteins by using distributed representations of RNA primary sequence and secondary structure.

BACKGROUND: RNA binding proteins (RBPs) play a vital role in post-transcriptional processes in all eukaryotes, such as splicing regulation, mRNA trans...

The effect of topical application of meloxicam on inflamed dental pulp.

BACKGROUND/PURPOSE: Effective regulation of the inflammatory process is essential for pulp repair and regeneration. Meloxicam has anti-inflammatory ac...

Challenges in the Development, Deployment, and Regulation of Artificial Intelligence in Anatomic Pathology.

Significant advances in artificial intelligence (AI), deep learning, and other machine-learning approaches have been made in recent years, with applic...