Publications by authors named "A V Shmelev"

Recent advancements in genomics, propelled by artificial intelligence, have unlocked unprecedented capabilities in interpreting genomic sequences, mitigating the need for exhaustive experimental analysis of complex, intertwined molecular processes inherent in DNA function. A significant challenge, however, resides in accurately decoding genomic sequences, which inherently involves comprehending rich contextual information dispersed across thousands of nucleotides. To address this need, we introduce GENA language model (GENA-LM), a suite of transformer-based foundational DNA language models capable of handling input lengths up to 36 000 base pairs.

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Background: In-hospital mortality rates following all types of pancreatic resections (PRs) have decreased over recent decades. Our aim was to identify predictors of in-hospital mortality following pancreatic resection.

Methods: All patients undergoing pancreatic resection were sampled from the National Inpatient Sample (NIS) in the years 2007-2012.

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The COVID-19 pandemic has transformed health care delivery through the rise of telehealth solutions. Though telemedicine-based care has been identified as safe and feasible in postoperative care, data on initial surgical consultations in the preoperative setting are lacking. We sought to compare patient characteristics, anticipated downstream care utilization, and patient-reported experiences (PREs) for in-person versus telemedicine-based care conducted for initial consultation encounters at a hernia and abdominal wall center.

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Background: It is increasingly recognized that complex abdominal wall reconstruction (cAWR) necessitates specialized training. No studies have been conducted to assess whether a volume-outcomes relationship is present in cAWR. We sought to determine if outcomes for patients undergoing cAWR varied based on surgeon volume among participants in the Abdominal Core Health Quality Collaborative (ACHQC).

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We present the results of the luminescence response studies of a single YVO:Yb, Er particle of 1-µm size. Yttrium vanadate nanoparticles are well-known for their low sensitivity to surface quenchers in water solutions which makes them of special interest for biological applications. First, YVO:Yb, Er nanoparticles (in the size range from 0.

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