Publications by authors named "Lavi Erisson"

Article Synopsis
  • Researchers developed a machine learning model to predict endoscopic disease activity levels in ulcerative colitis by analyzing full-length procedure videos.
  • The model utilized data from 793 videos, achieving high accuracy in distinguishing between inactive and active endoscopic disease in tests.
  • Results showed strong performance metrics, with the model reaching up to 92% area under the curve and 89% accuracy in independent test sets, indicating its potential for improving assessment consistency.
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 Detecting colorectal neoplasia is the goal of high-quality screening and surveillance colonoscopy, as reflected by high adenoma detection rate (ADR) and adenomas per colonoscopy (APC). The aim of our study was to evaluate the performance of a novel artificial intelligence (AI)-aided polyp detection device, Skout, with the primary endpoints of ADR and APC in routine colonoscopy.  We compared ADR and APC in a cohort of outpatients undergoing routine high-resolution colonoscopy with and without the use of a real-time, AI-aided polyp detection device.

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Aims: SD-1077, a selectively deuterated precursor of dopamine (DA) structurally related to L-3,4-dihydroxyphenylalanine (L-DOPA), is under development for treatment of motor symptoms of Parkinson's disease. Preclinical models have shown slower metabolism of central deuterated DA. The present study investigated the peripheral pharmacokinetics (PK), metabolism and safety of SD-1077.

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Aims: Custirsen (OGX-011/TV-1011), a second-generation antisense oligonucleotide (ASO) that reduces clusterin production, is under investigation with chemotherapy in patients with solid tumours. Custirsen is associated with constitutional symptoms (CS) that may interfere with clinical pharmacology investigations, such as QT interval studies. Experience with other ASOs suggests NSAID premedication may ameliorate CS, but we observed suboptimal outcomes in healthy subjects given custirsen and NSAIDs.

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