Anastomotic Stricture Definition After Esophageal Atresia Repair: Role of Endoscopic Stricture Index

Parente, Giovanni; Gargano, Tommaso; Ruggeri, Giovanni; Maffi, Michela; D’Antonio, Simone; Sacchet, Elisa; Lima, Mario

doi:10.1016/j.jss.2020.08.035

Cited by 15 publications

(6 citation statements)

References 18 publications

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“…Esophageal food impaction (EFI) in children is mostly secondary to comorbidities, such as anastomotic stenosis after esophageal atresia repair, eosinophilic esophagitis (EoE), reflux esophagitis, or, rarely, achalasia [13,14]. The most common symptoms are sialorrhea, dysphagia, odynophagia, and epigastric pain.…”

Section: Esophageal Food Impactionmentioning

confidence: 99%

Ask Doctor Smartphone! An App to Help Physicians Manage Foreign Body Ingestions in Children

Di Mitri,

Parente,

Bisanti

et al. 2023

Diagnostics

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Background: Foreign body ingestion (FBI) represents the most common cause of emergent gastrointestinal endoscopy in children. FBI’s management can be quite challenging for physicians because of the variability of the clinical presentation, and the decision tree becomes even more intricate because of patient-specific variables that must be considered in the pediatric age range (e.g., age of patients and neuropsychiatric disorders) in addition to the mere characteristics of the foreign body. We present an application for smartphones designed for pediatricians and pediatric surgeons based on the latest guidelines from the official pediatric societies. The app aims to help physicians manage FBI quickly and properly in children. Materials and methods: The latest pediatric FBI management guidelines were reviewed and summarized. The flow chart we obtained guided the development of a smartphone application. A questionnaire was administered to all pediatric surgeon trainees at our institute to test the feasibility and helpfulness of the application. Results: An app for smartphones was obtained and shared for free on the Google Play Store and Apple Store. The app guides the physician step by step in the diagnostic process, analyzing all patient- and foreign body-specific characteristics. The app consultation ends with a suggestion of the most proper decision to make in terms of further radiological investigations and the indication and timing of endoscopy. A questionnaire administered to trainees proved the app to be useful and easy to use. Conclusion: We developed an app able to help pediatricians and pediatric surgeons manage FBI in children, providing standardized and updated recommendations in a smart and easily available way.

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Section: Esophageal Food Impactionmentioning

confidence: 99%

Ask Doctor Smartphone! An App to Help Physicians Manage Foreign Body Ingestions in Children

Di Mitri,

Parente,

Bisanti

et al. 2023

Diagnostics

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“…The Type 2 diabetes can be managed with proper diet, exercise, and a healthy lifestyle [7] . DM and its complications lead to diabetic retinopathy (DR) [8] , [37] , [38] . DM is derived from the Latin term mellitus, which means sweet, and the Greek word diabetes, which means to syphon or pass through.…”

Section: Introductionmentioning

confidence: 99%

ExpACVO-Hybrid Deep learning: Exponential Anti Corona Virus Optimization enabled Hybrid Deep learning for tongue image segmentation towards diabetes mellitus detection

Mathew

Sathyalakshmi

2023

Biomedical Signal Processing and Control

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“…Strength and polarity are specified, in sentiment dictionaries, using corpus words and phrases [12]. The entire process is relied upon for boosting sales and creating product rankings [19], [20].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Rider Feedback Artificial Tree Optimization-Based Deep Neuro-Fuzzy Network for Classification of Sentiment Grade

Jasti¹,

Kumar²

2023

JTIT

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Sentiment analysis is an efficient technique for expressing users’ opinions (neutral, negative or positive) regarding specific services or products. One of the important benefits of analyzing sentiment is in appraising the comments that users provide or service providers or services. In this work, a solution known as adaptive rider feedback artificial tree optimization-based deep neuro-fuzzy network (RFATO-based DNFN) is implemented for efficient sentiment grade classification. Here, the input is pre-processed by employing the process of stemming and stop word removal. Then, important factors, e.g. SentiWordNet-based features, such as the mean value, variance, as well as kurtosis, spam word-based features, term frequency-inverse document frequency (TF-IDF) features and emoticon-based features, are extracted. In addition, angular similarity and the decision tree model are employed for grouping the reviewed data into specific sets. Next, the deep neuro-fuzzy network (DNFN) classifier is used to classify the sentiment grade. The proposed adaptive rider feedback artificial tree optimization (A-RFATO) approach is utilized for the training of DNFN. The A-RFATO technique is a combination of the feedback artificial tree (FAT) approach and the rider optimization algorithm (ROA) with an adaptive concept. The effectiveness of the proposed A-RFATO-based DNFN model is evaluated based on such metrics as sensitivity, accuracy, specificity, and precision. The sentiment grade classification method developed achieves better sensitivity, accuracy, specificity, and precision rates when compared with existing approaches based on Large Movie Review Dataset, Datafiniti Product Database, and Amazon reviews.

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Anastomotic Stricture Definition After Esophageal Atresia Repair: Role of Endoscopic Stricture Index

Cited by 15 publications

References 18 publications

Ask Doctor Smartphone! An App to Help Physicians Manage Foreign Body Ingestions in Children

Ask Doctor Smartphone! An App to Help Physicians Manage Foreign Body Ingestions in Children

ExpACVO-Hybrid Deep learning: Exponential Anti Corona Virus Optimization enabled Hybrid Deep learning for tongue image segmentation towards diabetes mellitus detection

Adaptive Rider Feedback Artificial Tree Optimization-Based Deep Neuro-Fuzzy Network for Classification of Sentiment Grade

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