FDA General

A hybrid deep learning framework for gene regulatory network inference from single-cell transcriptomic data.

Inferring gene regulatory networks (GRNs) based on gene expression profiles is able to provide an insight into a number of cellular phenotypes from the genomic level and reveal the essential laws underlying various life phenomena. Different from the bulk expression data, single-cell transcriptomic data embody cell-to-cell variance and diverse biological information, such as tissue characteristics,...

Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions.

New drug production, from target identification to marketing approval, takes over 12 years and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the urgent need for more powerful computational methods for drug discovery. Here, we review the computational approaches to predicting protein-ligand interactions in the context of drug discovery, focusing on methods using arti...

SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations.

MiRNAs are a class of small non-coding RNA molecules that play an important role in many biological processes, and determining miRNA-disease associati...

Fighting COVID-19 with Artificial Intelligence.

The development of vaccines for the treatment of COVID-19 is paving the way for new hope. Despite this, the risk of the virus mutating into a vaccine-...

Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors.

Artificial intelligence (AI) consists of a synergistic assembly of enhanced optimization strategies with wide application in drug discovery and develo...

Robot-assisted carotid artery stenting: outcomes, safety, and operational learning curve.

OBJECTIVE: Over the past 2 decades, robots have been increasingly used in surgeries to help overcome human limitations and perform precise and accurat...

Artificial Intelligence: Innovation to Assist in the Identification of Sono-anatomy for Ultrasound-Guided Regional Anaesthesia.

Ultrasound-guided regional anaesthesia (UGRA) involves the targeted deposition of local anaesthesia to inhibit the function of peripheral nerves. Ultr...

Artificial Intelligence for Precision Oncology.

Precision oncology is an innovative approach to cancer care in which diagnosis, prognosis, and treatment are informed by the individual patient's gene...

Clinical insights into hematologic malignancies and comparative analysis of molecular signatures of acute myeloid leukemia in different ethnicities using an artificial intelligence offering.

Next generation sequencing generates copious amounts of genomics data, causing manual interpretation to be laborious and non-scalable while remaining ...

Applications of Artificial Intelligence in Pediatric Oncology: A Systematic Review.

PURPOSE: There is a need for an improved understanding of clinical and biologic risk factors in pediatric cancer to improve patient outcomes. Machine ...

When Medical Devices Have a Mind of Their Own: The Challenges of Regulating Artificial Intelligence.

How can an agency like the U.S. Food & Drug Administration ("FDA") effectively regulate software that is constantly learning and adapting to real-worl...

[Protection effect of baicalin-regulated IKKα on inflammatory reaction of human oral keratinocytes].

PURPOSE: To observe the regulation of baicalin on IKKα mediated MASPIN in Human oral keratinocytes (HOKs) inflammatory reaction, this study was to exp...

Machine learning integrates genomic signatures for subclassification beyond primary and secondary acute myeloid leukemia.

Although genomic alterations drive the pathogenesis of acute myeloid leukemia (AML), traditional classifications are largely based on morphology, and ...

Prediction of RBP binding sites on circRNAs using an LSTM-based deep sequence learning architecture.

Circular RNAs (circRNAs) are widely expressed in highly diverged eukaryotes. Although circRNAs have been known for many years, their function remains ...

A Deep Learning Model with High Standalone Performance for Diagnosis of Unruptured Intracranial Aneurysm.

PURPOSE: This study aimed to investigate whether a deep learning model for automated detection of unruptured intracranial aneurysms on time-of-flight ...

Clinical Artificial Intelligence Applications in Radiology: Neuro.

Radiologists have been at the forefront of the digitization process in medicine. Artificial intelligence (AI) is a promising area of innovation, parti...

Regulatory Issues and Challenges to Artificial Intelligence Adoption.

Artificial intelligence technology promises to redefine the practice of radiology. However, it exists in a nascent phase and remains largely untested ...

Outcomes of Artificial Intelligence Volumetric Assessment of Kidneys and Renal Tumors for Preoperative Assessment of Nephron-Sparing Interventions.

Renal-cell carcinoma is the most common kidney cancer and the 13th most common cause of cancer death worldwide. Partial nephrectomy and percutaneous ...

Using machine learning to automate ultrasound-based classification of butt-fused joints in medium-density polyethylene gas pipes.

Polyethylene (PE) pipes are widely used in gas distribution. Their joints are prone to various flaws and are the most problematic part of the pipeline...

Research on automatic preprocessing equipment of salivary analyte for PCR inspection of coronavirus.

Polymerase chain reaction (PCR) inspection of salivary analyte is performed by pretreatment, RNA extraction setup, RNA extraction, PCR setup, and the ...