Publications by authors named "Jiaying You"

Background: Laparoscopic pancreatoduodenectomy (LPD) is one of the most challenging operations and has a long learning curve. Artificial intelligence (AI) automated surgical phase recognition in intraoperative videos has many potential applications in surgical education, helping shorten the learning curve, but no study has made this breakthrough in LPD. Herein, we aimed to build AI models to recognize the surgical phase in LPD and explore the performance characteristics of AI models.

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Background: Laparoscopic spleen-preserving distal pancreatectomy (LSPDP) is a widely adopted surgical approach for benign and low-grade malignant neoplasms of the distal pancreas. The Kimura and Warshaw techniques represent two principal strategies, yet it still needs to be determined which one is superior. Our investigation aimed to evaluate the clinical outcomes associated with each technique.

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Background: The fistula risk score (FRS) is the widely acknowledged prediction model for clinically relevant postoperative pancreatic fistula (CR-POPF). In addition, the alternative FRS (a-FRS) and updated alternative FRS (ua-FRS) have been developed. This study performed external validation and comparison of these 3 models in patients who underwent laparoscopic pancreaticoduodenectomy (LPD) with Bing's pancreaticojejunostomy.

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Introduction: Postoperative pancreatic fistula (POPF) remains one of the most severe complications of laparoscopic pancreaticoduodenectomy (LPD). Theoretically, transecting the pancreatic neck more distally has both advantages (more blood supply, and more central pancreatic duct) and disadvantages (maybe smaller the pancreatic duct) in preventing POPF. This theoretical contradiction pushed us to organise this trial to explore the impact of the level of pancreatic transection in clinical practice.

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Background: Emerging studies indicated that circular RNA hsa_circ_ 0023404 and its target miR-217/MARK1 axis play a critical role in cancer progression such as non-small cell lung cancer and cervical cancer. However, the role of hsa_circ_0023404/miR-217/MARK1 involved in endometrial cancer (EC) was not investigated yet. The aim of this study is to investigate the functions of hsa_circ_0023404 in endometrial cancer (EC) and the potential molecular mechanism.

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Background: Due to varied surgical skills and the lack of an efficient rating system, we developed Surgesture based on elementary functional surgical gestures performed by surgeons, which could serve as objective metrics to evaluate surgical performance in laparoscopic cholecystectomy (LC).

Methods: We defined 14 LC basic Surgestures. Four surgeons annotated Surgestures among LC videos performed by experts and novices.

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Aging is considered an inevitable process that causes deleterious effects in the functioning and appearance of cells, tissues, and organs. Recent emergence of large-scale gene expression datasets and significant advances in machine learning techniques have enabled drug repurposing efforts in promoting longevity. In this work, we further developed our previous approach-DeepCOP, a quantitative chemogenomic model that predicts gene regulating effects, and extended its application across multiple cell lines presented in LINCS to predict aging gene regulating effects induced by small molecules.

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Background: Artificial intelligence and computer vision have revolutionized laparoscopic surgical video analysis. However, there is no multi-center study focused on deep learning-based laparoscopic cholecystectomy phases recognizing. This work aims to apply artificial intelligence in recognizing and analyzing phases in laparoscopic cholecystectomy videos from multiple centers.

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Currently, safety of laparoscopic pancreaticoduodenectomy (LPD) in patients with liver cirrhosis is unknown. The aim of this study was to explore postoperative morbidity and mortality and long-term outcomes of cirrhotic patients after LPD. The study was a one-center retrospective study comprising 353 patients who underwent LPD between October 2010 and December 2019.

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Background: Traditional methods for drug discovery are time-consuming and expensive, so efforts are being made to repurpose existing drugs. To find new ways for drug repurposing, many computational approaches have been proposed to predict drug-target interactions (DTIs). However, due to the high-dimensional nature of the data sets extracted from drugs and targets, traditional machine learning approaches, such as logistic regression analysis, cannot analyze these data sets efficiently.

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Background: The optimal treatment strategy for papillary thyroid microcarcinoma (PTMC) has remained controversial. The purpose of this study was to provide a new reference value for PTMC to aid the selection of optimal management for minute lesions.

Patients And Methods: A pool of 1176 consecutive patients who met the inclusion criteria were ultimately enrolled in this study.

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Background: Periprostatic adipose tissue (PPAT) has been recognized to associate with prostate cancer (PCa) aggressiveness and progression. Here, we sought to investigate whether excess adiposity modulates the methylome of PPAT in PCa patients. DNA methylation profiling was performed in PPAT from obese/overweight (OB/OW, BMI > 25 kg m) and normal weight (NW, BMI < 25 kg m) PCa patients.

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The multifocal papillary thyroid cancer (PTC), with more aggressive and poorer prognosis, is not rare in papillary histotype. Few studies evaluated risk factors and lymph node metastasis in multifocal PTC. The aim of this present study focusing on risk factors and lymph node metastasis characteristics in multifocal PTC was excepted to assist clinical decisions regarding surgery.

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Background: Recurrent laryngeal nerve (RLN) invasion in papillary thyroid carcinoma (PTC) is one of the main predictors of poor prognosis. The present study investigated the risk factors for RLN invasion in PTC patients.

Methods: A total of 3,236 patients who received thyroidectomy due to PTC in Thyroid and Parathyroid Surgery Center of West China Hospital of Sichuan University were reviewed.

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