《Intelligent Medicine》

作品数:116被引量:57H指数:3
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《Intelligent Medicine》
主办单位:中华医学会
最新期次:2024年4期更多>>
发文主题:INTELLIGENTMEDICINEMACHINE_LEARNINGINTERNETAUTHORS更多>>
发文领域:医药卫生自动化与计算机技术文化科学理学更多>>
发文基金:国家自然科学基金北京市自然科学基金The Royal Society广东省自然科学基金更多>>
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Blockchain for digital healthcare: Case studies and adoption challenges
《Intelligent Medicine》2024年第4期215-225,共11页Fei Zhou Yue Huang Chengquan Li Xiaobin Feng Wei Yin Guoyan Zhang Sisi Duan 
sponsored by the Tsinghua-Toyota Joint Research In-stitute Inter-disciplinary Program.
The healthcare industry is significantly transforming toward digital and smart healthcare.Blockchain,as an emerging distributed collaborative paradigm,offers a promising solution for ensuring trustworthiness and high ...
关键词:Blockchain Healthcare Data sharing 
Comparison of feature learning methods for non-invasive interstitial glucose prediction using wearable sensors in healthy cohorts:a pilot study
《Intelligent Medicine》2024年第4期226-238,共13页Xinyu Huang Franziska Schmelter Annemarie Uhlig Muhammad Tausif Irshad Muhammad Adeel Nisar Artur Piet Lennart Jablonski Oliver Witt Torsten Schroder Christian Sina Marcin Grzegorzek 
supported by DAMP Foundation,Germany(Grant No.2020-14).
Background Alterations in glucose metabolism,especially the postprandial glucose response(PPGR),are cru-cial contributors to metabolic dysfunction,which underlies the pathogenesis of metabolic syndrome.Personalized lo...
关键词:Non-invasive glucose monitoring Interstitial glucose prediction Deep learning Physiological signal processing Wearable sensors Clarke error grid 
Improving vertebral diagnosis in computed tomography scans:a clinically oriented attention-driven asymmetric convolution network for segmentation
《Intelligent Medicine》2024年第4期239-248,共10页Bo Wang Ruijie Wang Zongren Chen Qixiang Zhang Wan Yuwen Xia Liu 
supported by the Special Project of Doctoral Research Innovation Team of Guangdong Polytechnic of Science and Technology(Grant No.XJBS202301).
Objective Vertebral segmentation in computed tomography(CT)images remains an essential issue in medical image analysis,stemming from the variability in vertebral shapes,high complex deformations,and the inherent ambig...
关键词:Vertebral segmentation Computed tomography images Attention-driven Pyramid global context Asymmetric convolutional U-SHAPED 
Application of statistical shape models in orthopedics: a narrative review
《Intelligent Medicine》2024年第4期249-255,共7页Xingbo Cai Ying Wu Junshen Huang Long Wang Yongqing Xu Sheng Lu 
supported by the Yunnan Provincial Department of Science and Technology(Grant No.202401AU070121);Yunnan Orthopedics and Sports Rehabilitation Clinical Medicine Research Center(Grant No.202102AA310068);Yunnan Provincial Clinical Orthopaedic Trauma Medical Center(Second Cycle);Clinical Key Subject Construction Project of PLA;Medical Key Subject of Joint Logistic Support Force of PLA(Grant No.145AHQ146009000X);Yunnan Key Laboratory of Digital Orthopaedics.
Statistical shape models(SSMs)are effective for image processing and analysis and have been used in various medical fields,including face recognition and cranial bone recognition.In orthopedics,SSMs are being used in ...
关键词:Statistical shape analysis ORTHOPEDICS Automated diagnosis support Data reconstruction SEGMENTATION 
Few-shot learning based histopathological image classification of colorectal cancer
《Intelligent Medicine》2024年第4期256-267,共12页Rui Li Xiaoyan Li Hongzan Sun Jinzhu Yang Md Rahaman Marcin Grzegozek Tao Jiang Xinyu Huang Chen Li 
supported by National Natural Science Foundation of China(Grant No.82220108007);Liaoning Province Applied Basic Research Program(Grant No.2023JH2/101600016);Sichuan Science and Technology Planning Project(Grant No.2024YFHZ0320);Special Project for Traditional Chinese Medicine Research of Sichuan Administration of Traditional Chinese Medicine(Grant No.2024zd030).
Background Colorectal cancer is a prevalent and deadly disease worldwide,posing significant diagnostic challenges.Traditional histopathologic image classification is often inefficient and subjective.Although some hist...
关键词:Colorectal cancer Few-shot learning Transfer learning Contrastive learning Histopathological images Benign and malignant categories 
Computing,data,and the role of general practitioners and general practice in England
《Intelligent Medicine》2024年第4期268-274,共7页Malcolm J.Fisk 
This paper gave attention to two issues that arise because of the growth in the use of health data by general practitioners(GPs)and general practices in England.The issues were(a)the use and commercialisation of pa-ti...
关键词:Artificial intelligence Commercialisation General practice General practitioners Health data Scientification 
Challenges in standardizing image quality across diverse ultrasound devices
《Intelligent Medicine》2024年第4期275-275,共1页Rebeca Tenajas David Miraut 
Dear Editor,We read with great interest the article titled“Automated assessment of transthoracic echocardiogram image quality using deep neural networks”[1]that was recently published in Intelligent Medicine.As dedi...
关键词:networks NEURAL IMAGE 
Guide for Authors Intelligent Medicine
《Intelligent Medicine》2024年第4期276-282,共7页
Aim&Scopes.Intelligent Medicine is an open access,peer-reviewed journal sponsored and owned by the Chinese Medical Association and designated to publish high-quality original research and review articles from the inte...
关键词:artificial INTELLIGENT INTERNET 
The First Editorial Board of Intelligent Medicine
《Intelligent Medicine》2024年第3期I0001-I0001,共1页
Application of graph-curvature features in computer-aided diagnosis for histopathological image identification of gastric cancer
《Intelligent Medicine》2024年第3期141-152,共12页Ruilin He Chen Li Xinyi Yang Jinzhu Yang Tao Jiang Marcin Grzegorzek Hongzan Sun 
supported by the National Natural Science Foundation of China(Grant No.82220108007).
Background Histopathology diagnosis is often regarded as the final diagnostic method for malignant tumors;however,it has some drawbacks.This study explored a computer-aided diagnostic method that can be used to identi...
关键词:Gastric cancer Graph-curvature feature Image identification 
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