FDA General

Memory-Based Event-Triggered Output Regulation for Networked Switched Systems With Unstable Switching Dynamics.

This article studies an event-triggered asynchronous output regulation problem (EAORP) for networked switched systems (NSSs) with unstable switching dynamics (USDs) including all modes unstable and partial switching instants destabilization, which means that the Lyapunov function increases both on the activation intervals of all subsystems and at some switching instants. First, a memory-based mode...

Safe design of surgical robots - a systematic approach to comprehensive hazard identification.

OBJECTIVES: Since the 1980s, robotic arms have been transferred from industrial applications to orthopaedic surgical robotics. Adverse events are frequent and often associated with the adopted powerful and oversized anthropomorphic arms. The FDA's 510(k) pathway encourages building on such systems, leading to the adoption of hazards, which is known as "predicate creep". Additionally, the methodolo...

The Navigation System of a Logistics Inspection Robot Based on Multi-Sensor Fusion in a Complex Storage Environment.

To reliably realize the functions of autonomous navigation and cruise of logistics robots in a complex logistics storage environment, this paper propo...

Deep learning of cross-species single-cell landscapes identifies conserved regulatory programs underlying cell types.

Despite extensive efforts to generate and analyze reference genomes, genetic models to predict gene regulation and cell fate decisions are lacking for...

Applications of machine learning techniques for enhancing nondestructive food quality and safety detection.

In considering the need of people all over the world for high-quality food, there has been a recent increase in interest in the role of nondestructive...

Online Detection System for Wheat Machine Harvesting Impurity Rate Based on DeepLabV3.

Wheat, one of the most important food crops in the world, is usually harvested mechanically by combine harvesters. The impurity rate is one of the mos...

Systematic analysis of the test design and performance of AI/ML-based medical devices approved for triage/detection/diagnosis in the USA and Japan.

The development of computer-aided detection (CAD) using artificial intelligence (AI) and machine learning (ML) is rapidly evolving. Submission of AI/M...

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

The number of patients with heart failure and related deaths is rapidly increasing worldwide, making it a major problem. Cardiac hypertrophy is a cruc...

The current status and future of FDA-approved artificial intelligence tools in chest radiology in the United States.

Artificial intelligence (AI) is becoming more widespread within radiology. Capabilities that AI algorithms currently provide include detection, segmen...

A voting-based ensemble feature network for semiconductor wafer defect classification.

Semiconductor wafer defects severely affect product development. In order to reduce the occurrence of defects, it is necessary to identify why they oc...

Deep Learning-Based Medical Data Association Rules to Explore the Connectivity and Regulation Mechanism of miRNA-mRNA Network in Myocarditis.

Acute, chronic myocarditis as myocardial localized or diffuse inflammation lesions is usually involving cardiac function in patients with severe adver...

Marker-Independent Food Identification Enabled by Combing Machine Learning Algorithms with Comprehensive GC × GC/TOF-MS.

Reliable methods are always greatly desired for the practice of food inspection. Currently, most food inspection techniques are mainly dependent on th...

Deep Learning-Based Nuclear Morphometry Reveals an Independent Prognostic Factor in Mantle Cell Lymphoma.

Blastoid/pleomorphic morphology is associated with short survival in mantle cell lymphoma (MCL), but its prognostic value is overridden by Ki-67 in mu...

CPV of the Future: AI-Powered Continued Process Verification for Bioreactor Processes.

According to the standard guidelines by the FDA, process validation in biopharma manufacturing encompasses a life cycle consisting of three stages: pr...

Automatic Meter Reading from UAV Inspection Photos in the Substation by Combining YOLOv5s and DeeplabV3.

The combination of unmanned aerial vehicles (UAVs) and artificial intelligence is significant and is a key topic in recent substation inspection appli...

The regulation of artificial intelligence for health in Brazil begins with the General Personal Data Protection Law.

Artificial intelligence develops rapidly and health is one of the areas where new technologies in this field are most promising. The use of artificial...

Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology.

Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pat...

Deep Learning Assistance Closes the Accuracy Gap in Fracture Detection Across Clinician Types.

BACKGROUND: Missed fractures are the most common diagnostic errors in musculoskeletal imaging and can result in treatment delays and preventable morbi...

Adverse events in the digital age and where to find them.

Exponential growth of health-related data collected by digital tools is a reality within pharmaceutical and medical device research and development. D...

Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.

In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identi...