Results 1 to 10 of about 159,777 (173)

Effectiveness of AI-enhanced colonoscopy: A case-control study using real world evidence in a young screening age population [PDF]

open access: yesThe Saudi Journal of Gastroenterology
Background:Computer aided detection (CADe) colonoscopy has been shown in randomized controlled trials to improve detection of adenomatous colorectal polyps. However, in real-world settings the benefits are less clear.
Maryam A. Alahmad   +10 more
doaj   +2 more sources

Integration of Endocuff‐Assisted and Computer‐Aided Colonoscopy: A Meta‐Analysis of Randomized Controlled Trials [PDF]

open access: yesJGH Open
Introduction Colorectal cancer (CRC) is a leading cause of cancer‐related deaths, with missed lesions during colonoscopy contributing to increased mortality.
Umar Akram   +8 more
doaj   +2 more sources

Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled Trial [PDF]

open access: yesGut and Liver
Background/Aims : Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems have been introduced to increase the polyp detection rate (PDR) during colonoscopy, potentially enhancing
Han Jo Jeon   +10 more
doaj   +2 more sources

A novel cloud-based artificial intelligence for real-time detection of colorectal neoplasia – a randomized controlled trial (EAGLE) [PDF]

open access: yesnpj Digital Medicine
Previously, colorectal polyp computer-aided detection (CADe) systems required on-site high-performance hardware installations (e.g., FPGAs/GPUs), creating practical challenges to upgrades and tying hospitals to legacy hardware. Cloud-based CADe solutions
Rawen Kader   +12 more
doaj   +2 more sources

Evaluation of computer-aided detection for gastric cancer using white-light and linked-color imaging: a pilot study [PDF]

open access: yesiGIE
Background and Aims: In recent years, the field of endoscopic artificial intelligence has seen significant advancements, largely because of the widespread implementation of deep learning techniques.
Takeshi Yasuda, MD, PhD   +11 more
doaj   +2 more sources

A comparative study benchmarking colon polyp with computer‐aided detection (CADe) software

open access: yesDEN Open
Background and aims Computer‐aided detection software (CADe) has shown promising results in real‐time polyp detection, but a limited head‐to‐head comparison of the available CADe systems has been performed.
Nikolaos Papachrysos   +11 more
exaly   +2 more sources

A retrospective cohort study evaluating the impact of computer-aided detection on adenoma and polyp detection rates among nongastroenterologist endoscopists in a rural medical center [PDF]

open access: yesiGIE
Background and Aims: Disproportionate increases in colorectal cancer (CRC) morbidity and mortality have been documented in rural communities, even when adjusted for race, ethnicity, and socioeconomic status.
Pierce L. Claassen, MD   +4 more
doaj   +2 more sources

O Abuso de Poder Regulatório:

open access: yesRevista de Defesa da Concorrência, 2021
O presente artigo aborda o abuso do poder regulatório, previsto no artigo 4º da nova Lei de Liberdade Econômica (Lei 13.874/19), como uma evolução da advocacia da concorrência no Brasil. Para isso foi abordada uma visão teórica das normas regulatórias e
Dario da Silva Oliveira Neto   +1 more
doaj   +1 more source

Nitric oxide-inhibited chloride transport in cortical thick ascending limbs is reversed by 8-iso-prostaglandin-F2α [PDF]

open access: yesKidney Research and Clinical Practice, 2022
Background Sodium chloride (NaCl) reabsorption in the cortical thick ascending limb (cTAL) is regulated by opposing effects. Nitric oxide (NO) inhibits NaCl reabsorption while 8-iso-prostaglandin-F2α (8-iso-PGF2α) stimulates it. Their interaction has not
Pablo D. Cabral   +5 more
doaj   +1 more source

Detection of epileptic seizures in EEG by using machine learning techniques

open access: yesDiagnostyka, 2023
In this research a public dataset of recordings of EEG signals of healthy subjects and epileptic patients was used to build three simple classifiers with low time complexity, these are decision tree, random forest and AdaBoost algorithm.
Muayed S AL-Huseiny, Ahmed S. Sajit
doaj   +1 more source

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