Artificial intelligence (AI) to enhance breast cancer screening: protocol for population-based cohort study of cancer detection by M Luke Marinovich, Gavin F Pereira, Nehmat Houssami, Elizabeth Wylie, Sophia Zackrisson, Stacy M Carter, Meagan Brennan, Alison Pearce, William Lotter, Helen Lund, Andrew Waddell, Jiye G Kim, Christoph I Lee

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Artificial Intelligence–Aided Diagnosis System for the Detection and Classification of Private-Part Skin Diseases: Decision Analytical Modeling Study by Wei Wang, Xiang Chen, Licong Xu, Kai Huang, Shuang Zhao, Yong Wang

“…This system provides the final diagnosis result by simulating the diagnostic process of dermatologists. Compared with existing advanced algorithms, this system is more accurate in identifying PPSDs. …”
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Interstitial cystitis or bladder pain syndrome: a modern view of a problem by V. F. Onopko, E. A. Kirilenko, E. O. Baranova, V. S. Golubeva

“…The review of domestic and foreign literary sources for 2002-2014 made it possible to deepen into the problem of interstitial cystitis and put together different points of view and also to systematize the store of knowledge. …”
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Exploring the limits of scan time reduction for ferumoxytol-enhanced whole-heart angiography in congenital heart disease patients by Ludovica Romanin, Milan Prsa, Christopher W. Roy, Xavier Sieber, Jérôme Yerly, Bastien Milani, Tobias Rutz, Salim Si-mohamed, Estelle Tenisch, Davide Piccini, Matthias Stuber

“…A similarity-driven multi-dimensional binning algorithm (SIMBA) was introduced for 3D whole-heart angiography from ferumoxytol-enhanced free-running MRI. …”
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Radiomics model building from multiparametric MRI to predict Ki-67 expression in patients with primary central nervous system lymphomas: a multicenter study by Yelong Shen, Siyu Wu, Yanan Wu, Chao Cui, Haiou Li, Shuang Yang, Xuejun Liu, Xingzhi Chen, Chencui Huang, Ximing Wang

“…The radiomics features were extracted respectively, and the features were screened by machine learning algorithm and statistical method. Radiomics models of seven different sequence permutations were constructed. …”
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A cross-sectional study of evaluating cervical spondylotic myelopathy based on gait and plantar pressures by Xuhong Zhang, Zichuan Wu, Hanlin Song, Aochen Xu, Junbin Liu, Junzhe Sheng, Baifeng Sun, Min Qi, Chen Xu, Yang Liu

“…Objective To examine the differences in gait patterns between cervical spondylotic myelopathy (CSM) patients and normal controls using visual recognition-based gait analysis and plantar pressure techniques, and to further analyze the differences in gait between different levels of disease severity as well as between gender groups. …”
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Prediction of induction chemotherapy efficacy in patients with locally advanced nasopharyngeal carcinoma using habitat subregions derived from multi-modal MRI radiomics by Mulan Pan, Lu Lu, Xingyu Mu, Xingyu Mu, Guanqiao Jin

“…The K-means clustering algorithm was utilized to segment the tumor into five distinct habitat subregions based on imaging features. …”
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A new era in treatment of cardiac amyloidosis: an overview of the Congress of cardiology by I. E. Strelkova

“…Advent of the first drug specific for treatment of transthyretin amyloid cardiomyopathy in Russia increased a need of awareness of ATTR-CM among general practitioners  and cardiologists, and introduction of modern diagnostic algorithms for this disease. Timely detection and competent differential diagnosis of ATTR-CM from other types of amyloid cardiomyopathy  can play a decisive role in the prognosis of this disease. …”
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Summary of updates to the 2021 European Society of Cardiology Guidelines for the diagnosis and treatment of acute and chronic heart failure by V. N. Larina, I. K. Skiba, A. S. Skiba

“…The article discusses the diagnostic criteria for different heart failure phenotypes, the potential of treating patients with heart failure mildly reduced and preserved ejection fraction.…”
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Application of artificial intelligence technologies for the detection of early childhood caries by Priyanka A, Rishi Sreekumar, S Namasivaya Naveen

“…This study examined various approaches, datasets, methodologies, and algorithms. The inclusion criteria are the accuracy of models, the investigation of different risk factors, and the applicability of ML and DL in caries prediction. …”
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A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach by Yuli Wang, Na Mei, Ziyi Zhou, Yuan Fang, Jiacheng Lin, Fanchen Zhao, Zhihong Fang, Yan Li

“…Abstract Background Lung cancer is characterized by high morbidity and mortality due to the lack of practical early diagnostic and prognostic tools. The present study uses machine learning algorithms to construct a clinical predictive model for non-small cell lung cancer (NSCLC) patients. …”
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State of affairs of tuberculosis in prison facilities: a systematic review of screening practices and recommendations for best TB control. by Natalie V S Vinkeles Melchers, Sabine L van Elsland, Joep M A Lange, Martien W Borgdorff, Jan van den Hombergh

“…<h4>Discussion</h4>TB screening algorithms differ by income area and should be adapted to local contexts. …”
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High sensitivity in spontaneous intracranial hemorrhage detection from emergency head CT scans using ensemble-learning approach by Juuso Takala, Heikki Peura, Riku Pirinen, Katri Väätäinen, Sergei Terjajev, Ziyuan Lin, Rahul Raj, Miikka Korja

“…Although the success of DL algorithms depends on multiple factors, including training data versatility and quality of annotations, using the proposed ensemble-learning approach and rule-based post-processing may help clinicians to develop highly accurate DL solutions for clinical imaging diagnostics.…”
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Non-Invasive Continuous Respiratory Monitoring on General Hospital Wards: A Systematic Review. by Kim van Loon, Bas van Zaane, Els J Bosch, Cor J Kalkman, Linda M Peelen

“…<h4>Data synthesis</h4>Six intervention and five diagnostic studies were included, evaluating the use of eight different devices for continuous respiratory monitoring. …”
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Functional state of the pancreas in adolescents with peptic ulcer of duodenum by I. S. Lembryk

“…In addition to conventional diagnostic algorithm for duodenal ulcer and pancreatic diseases the sonography with detailed visualization of the pancreas by method of B. …”
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Non‐Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints and Machine Learning by Ruiyuan Weng, Yudian Xu, Xinjie Gao, Linlin Cao, Jiabin Su, Heng Yang, He Li, Chenhuan Ding, Jun Pu, Meng Zhang, Jiheng Hao, Wei Xu, Wei Ni, Kun Qian, Yuxiang Gu

“…To address this issue, nanoparticle‐enhanced laser desorption/ionization mass spectrometry (LDI MS) was employed to record serum metabolic fingerprints (SMFs) with the aim of establishing a non‐invasive diagnosis method for MMD. Subsequently, a diagnostic model was developed based on deep learning algorithms, which exhibited high accuracy in differentiating the MMD group from the HC group (AUC = 0.958, 95% CI of 0.911 to 1.000). …”
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Fault Diagnosis Across Aircraft Systems Using Image Recognition and Transfer Learning by Lilin Jia, Cordelia Mattuvarkuzhali Ezhilarasu, Ian K. Jennions

“…However, current fault diagnosis algorithms require abundant and balanced data to be trained, which is difficult and expensive to obtain for aircraft systems. …”
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Automated Vertebral Bone Quality Determination from T1-Weighted Lumbar Spine MRI Data Using a Hybrid Convolutional Neural Network–Transformer Neural Network by Kristian Stojšić, Dina Miletić Rigo, Slaven Jurković

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Classification of mammograms: Comparing a graphical to a geometrical approach by Anirban Ghosh, Priya Ranjan, Kumar Dron Shrivastav, Rajiv Janardhanan

“…However, manual analysis is labor-intensive and prone to diagnostic errors. In this scenario, the large-scale deployment of computer-aided diagnosis using well-trained algorithms could significantly reduce the morbidity and mortality associated with this carcinoma. …”
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Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features by Jingna Tao, Zhongmian Zhang, Linghan Meng, Liju Zhang, Jiaqi Wang, Zhihong Li

“…BackgroundThis study aimed to construct and validate diagnostic models for the Operative Link on Gastritis Assessment (OLGA) and Operative Link on Gastric Intestinal Metaplasia Assessment (OLGIM) staging systems using three different methodologies based on magnifying endoscopy with narrow-band imaging (ME-NBI) features, to evaluate model performance, and to analyse risk factors for high-risk OLGA/OLGIM stages.MethodsWe enrolled 356 patients who underwent white-light endoscopy and ME-NBI at the Department of Gastroenterology, Dongzhimen Hospital, Beijing University of Chinese Medicine, between January 2022 and September 2023. …”
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