In modern medicine,medical image examination has become an important method and tool to deal with clinical diseases.The inherent defects of artificial analysis of medical images make medical images become the most val...In modern medicine,medical image examination has become an important method and tool to deal with clinical diseases.The inherent defects of artificial analysis of medical images make medical images become the most valuable application scenario of artificial intelligence(AI).This paper aims at how to effectively adapt to economic development and cultivate talents who combine artificial intelligence and medicine,which is a difficult problem and challenge facing schools and educators.A new AI+medical imaging talent training model was proposed,and suggestions for improvement were introduced from the course design,assessment system,faculty team,and course textbooks,and the teaching effect was explained through the training process,supporting conditions,and training mechanism,so as to promote the scientific and technological progress of colleges and universities.and development.展开更多
Rectal cancer(RC)is one of the most common cancers worldwide.RC has high morbidity and mortality rates,with locally advanced rectal cancer(LARC)accounting for>30%of cases.Patients with LARC are routinely treated wi...Rectal cancer(RC)is one of the most common cancers worldwide.RC has high morbidity and mortality rates,with locally advanced rectal cancer(LARC)accounting for>30%of cases.Patients with LARC are routinely treated with neoadjuvant chemoradiotherapy(nCRT)but treatment outcomes vary greatly.It is crucial to predict and evaluate patient response to nCRT as early as possible.Radiomics is a potentially useful and non-invasive tool for clinical applications in different types of cancer including colorectal cancer.Radiomics has recently been used to predict treatment outcomes and many published studies have demonstrated the efficacy of radiomics.This review will discuss the application of radiomics in predicting of LARC response to nCRT and provide new insight for corollary studies.展开更多
文摘In modern medicine,medical image examination has become an important method and tool to deal with clinical diseases.The inherent defects of artificial analysis of medical images make medical images become the most valuable application scenario of artificial intelligence(AI).This paper aims at how to effectively adapt to economic development and cultivate talents who combine artificial intelligence and medicine,which is a difficult problem and challenge facing schools and educators.A new AI+medical imaging talent training model was proposed,and suggestions for improvement were introduced from the course design,assessment system,faculty team,and course textbooks,and the teaching effect was explained through the training process,supporting conditions,and training mechanism,so as to promote the scientific and technological progress of colleges and universities.and development.
基金supported by the Major Program Co-sponsored by Province and Ministry(WKJ-ZJ-2210).
文摘Rectal cancer(RC)is one of the most common cancers worldwide.RC has high morbidity and mortality rates,with locally advanced rectal cancer(LARC)accounting for>30%of cases.Patients with LARC are routinely treated with neoadjuvant chemoradiotherapy(nCRT)but treatment outcomes vary greatly.It is crucial to predict and evaluate patient response to nCRT as early as possible.Radiomics is a potentially useful and non-invasive tool for clinical applications in different types of cancer including colorectal cancer.Radiomics has recently been used to predict treatment outcomes and many published studies have demonstrated the efficacy of radiomics.This review will discuss the application of radiomics in predicting of LARC response to nCRT and provide new insight for corollary studies.
