Results 71 to 80 of about 5,226,528 (353)

Hallucinations in medical devices

open access: yesArtificial Intelligence in the Life Sciences
Computer methods in medical devices are frequently imperfect and are known to produce errors in clinical or diagnostic tasks. However, when deep learning and data-based approaches yield output that exhibit errors, the devices are frequently said to ...
Jason Granstedt   +4 more
doaj   +1 more source

Transcriptional profiling of circulating extracellular vesicles from prebiopsy prostate cancer patients

open access: yesMolecular Oncology, EarlyView.
RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner   +14 more
wiley   +1 more source

A Hybrid Reverse Learning Particle Swarm Optimization Method for Aircraft Maintenance Scheduling Based on the Resource-Constrained Project Scheduling Problem Model

open access: yesMachines
Aircraft maintenance scheduling is a critical task in air transportation and national defense security, characterized by complex multi-step procedures, strict precedence dependencies, and multi-resource constraints involving personnel skills and ...
Jiyan Zeng   +6 more
doaj   +1 more source

Adaptor protein CIN85 potentiates the motility of osteosarcoma cells via the Akt/mTOR and MMP2‐COL3A1 axis

open access: yesMolecular Oncology, EarlyView.
CIN85 is highly expressed in osteosarcoma, particularly in metastatic lesions. Its overexpression increases cell migration and Matrigel invasion, while silencing CIN85 suppresses these behaviors. Transcriptome analysis shows that CIN85 regulates MMP2, COL3A1, and Akt/mTOR signaling. Targeting these pathways reverses CIN85‐induced motility, highlighting
Iryna Horak   +10 more
wiley   +1 more source

Longitudinal circulating tumor DNA profiling in patients with advanced endometrial cancer using an off‐the‐shelf targeted NGS panel

open access: yesMolecular Oncology, EarlyView.
Intratumour heterogeneity complicates precision management of advanced endometrial cancer. Circulating tumor DNA (ctDNA) offers a minimally invasive strategy to capture tumor evolution and therapeutic resistance. Here, we compare tumor‐agnostic NGS with tumor‐informed ddPCR, outlining their relative sensitivity, concordance, and clinical implications ...
Carlos Casas‐Arozamena   +15 more
wiley   +1 more source

Federated semi-supervised learning based on feature alignment and knowledge distillation

open access: yesFrontiers in Physics
IntroductionRecently, federated learning has been successfully applied in fields related to cyber-physical-social systems (CPSSs), owing to its ability to harness decentralized clients for training a global model while ensuring data privacy. The existing
Zhe Ding   +11 more
doaj   +1 more source

Clinical performance of the urine‐based TERT promoter AbsoluteQ Digital PCR for non‐invasive detection of bladder cancer

open access: yesMolecular Oncology, EarlyView.
A urine‐based digital PCR assay targeting two hotspot TERT promoter variants detected bladder cancer with high sensitivity and no false positives in this case–control cohort. The streamlined AbsoluteQ workflow outperformed Sanger sequencing and supports non‐invasive molecular testing for bladder cancer detection.
Anna Nykel   +12 more
wiley   +1 more source

Scatter Removal in Photon-Counting Dual-Energy Chest X-Ray Imaging Using a Moving Block Method: A Simulation Phantom Study

open access: yesSensors
This work investigates the impact of scatter correction on photon-counting dual-energy chest radiography using a moving block method, focusing on quantifying improvements with the IEC 62220-2-1 dual-energy metrics.
Bahaa Ghammraoui, Yee Lam Elim Thompson
doaj   +1 more source

Software reliability prediction [PDF]

open access: yes
Two methods are proposed to find the maximum likelihood parameter estimates of a number of software reliability models. On the basis of the results from analysing 7 sets of real data, these methods are found to be both efficient and reliable.\ud \ud The simple approach of adapting software reliability predictions by Keiller and Littlewood (1984) can ...
openaire   +7 more sources

Confidence intervals for reliability growth models with small sample sizes [PDF]

open access: yes, 2003
Fully Bayesian approaches to analysis can be overly ambitious where there exist realistic limitations on the ability of experts to provide prior distributions for all relevant parameters.
Quigley, J.L., Walls, L.A.
core   +1 more source

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