Deep Web

BACKGROUND: Artificial intelligence (AI) techniques have been ascertained useful in the analysis and description of infectious areas in radiological images promptly. Our aim in this study was to design a web-based application for detecting and labeling infected tissues on CT (computed tomography) lung images of patients based on the deep learning (DL) method as a type of AI. MATERIALS AND METHODS: The U-Net architecture, one of the DL networks, is used as a hybrid model with pre-trained densely connected convolutional network 121 (DenseNet121) architecture for the segmentation process...

BACKGROUND AND AIMS: Obesity is a chronic disease which can cause severe metabolic disorders. Machine learning (ML) techniques, especially deep learning (DL), have proven to be useful in obesity research. However, there is a dearth of systematic reviews of DL applications in obesity. This article aims to summarize the current trend of DL usage in obesity research. METHODS: An extensive literature review was carried out across multiple databases, including PubMed, Embase, Web of Science, Scopus, and Medline, to collate relevant studies published from January 2018 to September 2023...

Many biological functions are mediated by large complexes formed by multiple proteins and other cellular macromolecules. Recent progress in experimental structure determination, as well as in integrative modeling and protein structure prediction using deep learning approaches, has resulted in a rapid increase in the number of solved multiprotein assemblies. However, the assembly process of large complexes from their components is much less well-studied. We introduce a rapid computational structure-based (SB) model, GoCa, that allows to follow the assembly process of large multiprotein complexes based on a known native structure...

BACKGROUND: Artificial intelligence (AI) models, clinical models (CM), and the integrated model (IM) are utilized to evaluate the response to neoadjuvant chemotherapy (NACT) in patients diagnosed with gastric cancer. OBJECTIVE: The objective is to identify the diagnostic test of the AI model and to compare the accuracy of AI, CM, and IM through a comprehensive summary of head-to-head comparative studies. METHODS: PubMed, Web of Science, Cochrane Library, and Embase were systematically searched until September 5, 2023, to compile English language studies without regional restrictions...

Lower extremity swelling may be broadly characterized as due to edema, lymphedema, or lipedema. Differentiation between these three conditions is important for providing appropriate treatment. This review analyzes and compares different clinical diagnostic modalities for these conditions, with the aim of assisting in the process of choosing the most appropriate diagnostic modality by highlighting the advantages and limitations of each. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for a systematic search of peer-reviewed literature, the following diagnostic methods for lower extremity swelling were investigated: (1) ultrasound (US), (2) lymphoscintigraphy (LSG), (3) computed tomography (CT), (4) bioimpedance spectroscopy (BIS), (5) tissue dielectric constant (TDC), and (6) magnetic resonance imaging (MRI), including magnetic resonance lymphangiography (MRL)...

A lot of underdeveloped nations, particularly in Africa, struggle with cancer-related, deadly diseases. Particularly in women, the incidence of breast cancer is rising daily because of ignorance and delayed diagnosis. Only by correctly identifying and diagnosing cancer in its very early stages of development can be effectively treated. The classification of cancer can be accelerated and automated with the aid of computer-aided diagnosis and medical image analysis techniques. This research provides the use of transfer learning from a Residual Network 18 (ResNet18) and Residual Network 34 (Resnet34) architectures to detect breast cancer...

BACKGROUND: Artificial intelligence (AI) systems have showed promising results in digital pathology, including digital nephropathology and specifically also kidney transplant pathology. AIM: Summarize the current state of research and limitations in the field of AI in kidney transplant pathology diagnostics and provide a future outlook. MATERIALS AND METHODS: Literature search in PubMed and Web of Science using the search terms "deep learning", "transplant", and "kidney"...

Prediction of the progression of knee osteoarthritis (KOA) is a very challenging task. Early identification of risk factors plays a vital role in diagnosing KOA. Thus, machine learning models are used to predict the progression of KOA. The purpose of the present study is to find out the efficacy of various machine learning models to identify the progression of KOA. A comprehensive literature search was conducted in international databases like Google Scholar, PubMed, Web of Science, and Scopus. Studies published from the year 2010 to May 2023 on the machine learning approach to diagnose KOA were included in the study...

INTRODUCTION: Radiologists have extensively employed the interpretation of chest X-rays (CXR) to identify visual markers indicative of COVID-19 infection, offering an alternative approach for the screening of infected individuals. This research article presents CovMediScanX, a deep learning-based framework designed for a rapid and automated diagnosis of COVID-19 from CXR scan images. METHODS: The proposed approach encompasses gathering and preprocessing CXR image datasets, training deep learning-based custom-made Convolutional Neural Network (CNN), pre-trained and hybrid transfer learning models, identifying the highest-performing model based on key evaluation metrics, and embedding this model into a web interface called CovMediScanX, designed for radiologists to detect the COVID-19 status in new CXR images...

OBJECTIVES: Aggressive (deep) angiomyxoma (AAM) is a rare mesenchymal tumor that typically originates from the vulvovaginal region, perineum, and pelvis in adult women. The objective of this case report and literature review is to comprehensively analyze the clinical, imaging, and pathological characteristics of atypical AAM in the female lower genital tract and pelvic floor in order to minimize preoperative misdiagnosis or missed diagnosis and ultimately optimize the clinical management strategy...

INTRODUCTION: Periodontitis is the main cause of tooth loss and is related to many systemic diseases. Artificial intelligence (AI) in periodontics has the potential to improve the accuracy of risk assessment and provide personalized treatment planning for patients with periodontitis. This systematic review aims to examine the actual evidence on the accuracy of various AI models in predicting periodontitis. METHODS: Using a mix of MeSH keywords and free text words pooled by Boolean operators ('AND', 'OR'), a search strategy without a time frame setting was conducted on the following databases: Web of Science, ProQuest, PubMed, Scopus, and IEEE Explore...

The intersection of precision medicine and artificial intelligence (AI) holds profound implications for cancer treatment, with the potential to significantly advance our understanding of drug responses based on the intricate architecture of tumor cells. A recent study by Park and colleagues titled "A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors," epitomizes this intersection by leveraging an interpretable deep learning model grounded in a comprehensive map of multiprotein assemblies in cancer, known as Nested Systems in Tumors (NeST)...

OBJECTIVES: To perform a comprehensive bibliometric analysis of global publications on the applications of artificial intelligence (AI) in cardiology. METHODS: Documents related to AI in cardiology published between 2002 and 2022 were retrieved from Web of Science Core Collection. R package "bibliometrix", VOSviewers and Microsoft Excel were applied to perform the bibliometric analysis. RESULTS: A total of 4332 articles were included. United States topped the list of countries publishing articles, followed by China and United Kingdom...

Artificial intelligence (AI) has extensive applications in a wide range of disciplines including healthcare and clinical practice. Advances in high-resolution whole-slide brightfield microscopy allow for the digitization of histologically stained tissue sections, producing gigapixel-scale whole-slide images (WSI). The significant improvement in computing and revolution of deep neural network (DNN)-based AI technologies over the last decade allow us to integrate massively parallelized computational power, cutting-edge AI algorithms, and big data storage, management, and processing...

BACKGROUND: Language and the ability to communicate effectively are key factors in mental health and well-being. Despite this critical importance, research on language is limited by the lack of a scalable phenotyping toolkit. METHODS: Here, we describe and showcase Lingo - a flexible online battery of language and nonverbal reasoning skills based on seven widely used tasks (COWAT, picture narration, vocal rhythm entrainment, rapid automatized naming, following directions, sentence repetition, and nonverbal reasoning)...

Deep learning-based methods for protein structure prediction have achieved unprecedented accuracy. Yet, their utility in the engineering of protein-based binders remains constrained due to a gap between the ability to predict the structures of candidate proteins and the ability to assess which of those proteins are more probable to bind to a target. To bridge this gap, we introduce Automated Pairwise Peptide-Receptor AnalysIs for Screening Engineered proteins (APPRAISE), a method for predicting the target binding propensity of engineered proteins...

OBJECTIVE: Optimal thromboprophylaxis in orthopaedic procedures is crucial in an attempt to lower the risk of venous thromboembolism, including deep vein thrombosis and pulmonary embolism. We aim to: 1) identify clinical practice guidelines (CPGs) and recommendations (CPRs) on thromboprophylaxis in adult patients undergoing orthopaedic procedures, and 2) assess the methodological quality and reporting clarity of these guidelines. METHODS: The study was conducted following the 2020 PRISMA guidelines for a systematic review and has been registered on the international prospective register of systematic reviews (PROSPERO) under the registration number (CRD42023406988)...

OBJECTIVE: Endovascular deep venous arterialization (DVA) is a novel technique aimed at salvaging peripheral arterial disease unamenable to conventional surgical intervention. This study aims to review contemporary literature on the efficacy, safety, and durability of DVA on patients with no-option critical limb ischaemia. METHODS: The study was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, using predefined search terms of "percutaneous deep vein arterialization" or "percutaneous deep venous arterialization" in PubMed, Web of Sciences, OvidSP, and EMBASE...

OBJECTIVE: To systematically review and conduct a meta-analysis to assess the effectiveness of dienogest (DNG) in the prolonged conservative drug management of deep infiltrating endometriosis (DIE). The findings from this study are intended to serve as a valuable reference for clinical decision-making regarding medication in the context of DIE. METHODS: Following the PRISMA Statement, we searched EMBASE, PubMed, The Cochrane Library, Web of Science, and Medline databases for relevant literature published in the public domain from the date of establishment of the database until October 2023...

BACKGROUND: Wrist arthroscopy technology is a surgical technology invented in recent years and widely used in clinical treatment of various wrist diseases. This study uses the methods of bibliometrics and visual analysis to understand the global research status, research hotspots, and future development trends of wrist arthroscopy. METHODS: The relevant literature of global publications on wrist arthroscopy from 2013 to 2023 was extracted from the Web of Science Core Collection database, and the annual output, cooperation, hot spots, research status, and development trend of this field were analyzed by using the bibliometric software (VOSviewers, CiteSpace, and the R package "Bibliometrix")...