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Identification of High-Risk Populations: The Cornerstone of Effective and Cost-Efficient cancer Screening

Biomedical and Environmental sciences 2025年第4期38卷 401-402页

作者： Wei Cao Fei Wang Ni Li Office of Cancer Screening National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Key Laboratory of Cancer Data Science National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China

cancer screening is a strategy focused on highrisk populations rather than universal populationwide screening, based on a comprehensive evaluation of epidemiological principles and practical feasibility. The effectiveness of screening depends on factors such as disease prevalence, as well as the sensitivity and specificity of the screening technology employed.

关键词： epidemiological principles practical feasibility cancer screening screening technology sensitivity high risk populations disease prevalence practical feasibility epidemiological principles

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cancer informatics 2023: data Sharing and Federating Learning Point Towards New Collaborative Opportunities

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Yearbook of Medical informatics 2023年第1期32卷 111-114页

作者： Warner, Jeremy L. Patt, Debra Department of Medicine Brown University Providence RI United States Director Center for Clinical Cancer Informatics and Data Science Legorreta Cancer Center Brown University Providence RI United States Vice President Texas Oncology Austin TX United States

OBJECTIVE: To summarize significant research contributions on cancer informatics published in 2022. METHODS: An extensive search using PubMed/MEDLINE was conducted to identify the scientific contributions published in 2022 that address topics in cancer informatics. The selection process comprised three steps: (i) ten candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of three best papers was conducted by the editorial board of the Yearbook. RESULTS: The three selected best papers demonstrate advances in federated learning, drug synergy prediction, and utilization of clinical note data. CONCLUSION: cancer informatics continues to mature as a subfield of biomedical informatics. Applications of informatics methods to data sharing and federated approaches are especially notable in 2022. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://***/licenses/by-nc-nd/4.

关键词： disparities health information technology informatics Neoplasms

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DMHFR:Decoder with Multi-Head Feature Receptors for Tract Image Segmentation

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Computers, Materials & Continua 2025年第3期82卷 4841-4862页

作者： Jianuo Huang Bohan Lai Weiye Qiu Caixu Xu Jie He Department of Endoscopy Center Zhongshan Hospital(Xiamen)Fudan UniversityXiamen361015China School of Computing and Data Science Xiamen University MalaysiaSepang43900Malaysia School of Computer Science and Techonology Tongji UniversityShanghai200092China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou UniversityWuzhou543002China Xiamen Clinical Research Center for Cancer Therapy Xiamen361015China

The self-attention mechanism of Transformers,which captures long-range contextual information,has demonstrated significant potential in image ***,their ability to learn local,contextual relationships between pixels requires further *** methods face challenges in efficiently managing multi-scale fea-tures of different granularities from the encoder backbone,leaving room for improvement in their global representation and feature extraction *** address these challenges,we propose a novel Decoder with Multi-Head Feature Receptors(DMHFR),which receives multi-scale features from the encoder backbone and organizes them into three feature groups with different granularities:coarse,fine-grained,and full *** groups are subsequently processed by Multi-Head Feature Receptors(MHFRs)after feature capture and modeling *** include two Three-Head Feature Receptors(THFRs)and one Four-Head Feature Receptor(FHFR).Each group of features is passed through these MHFRs and then fed into axial transformers,which help the model capture long-range dependencies within the *** three MHFRs produce three distinct feature *** output from the FHFR serves as auxiliary auxiliary features in the prediction head,and the prediction output and their losses will eventually be *** results show that the Transformer using DMHFR outperforms 15 state of the arts(SOTA)methods on five public ***,it achieved significant improvements in mean DICE scores over the classic Parallel Reverse Attention Network(PraNet)method,with gains of 4.1%,2.2%,1.4%,8.9%,and 16.3%on the CVC-ClinicDB,Kvasir-SEG,CVC-T,CVC-ColonDB,and ETIS-LaribPolypDB datasets,respectively.

关键词： Medical image segmentation feature exploration feature aggregation deep learning multi-head feature receptor

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Development of a Natural Language Processing Tool to Extract Acupuncture Point Location Terms 11

Development of a Natural Language Processing Tool to Extract...

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11th IEEE International Conference on Healthcare informatics, ICHI 2023

作者： Li, Yiming Peng, Xueqing Li, Jianfu Peng, Suyuan Pei, Donghong Tao, Cui Xu, Hua Hong, Na The University of Texas Health Science Center at Houston School of Biomedical Informatics HoustonTX United States Yale University Section of Biomedical Informatics and Data Science School of Medicine New HavenCT United States Peking University National Institute of Health Data Science Beijing China The University of Texas Md Anderson Cancer Center HoustonTX United States

ISBN: (纸本)9798350302639

Acupuncture point location information is significant to the effect of acupuncture therapy. A wealth of knowledge related to acupuncture point locations is typically dispersed across books or reports in free-text format, which can pose challenges for machines to understand and facilitate. In this study, our purpose is to develop a natural language processing (NLP) tool to extract acupuncture point location information. We adopted the World Health Organization (WHO) Standard Acupuncture Point Locations in the Western Pacific Region (WHO Standard) as our reference standard and corpus. Our proposed approach to develop and validate the NLP tool involves three key steps: 1) We leveraged pre-existing terminologies from the anatomy domain, specifically the International Anatomical Terminology (IAT) and Uber-anatomy Ontology (UBERON), to construct a baseline dictionary of acupoint locations. This dictionary was then used in conjunction with a dictionary lookup method to match terms in the acupuncture location descriptions outlined by the WHO Standard;2) We employed NLP models based on machine learning and deep learning techniques, specifically utilizing Conditional Random Fields (CRFs) and Recurrent Neural Network (RNN) for training. The CRFs and RNN models achieved overall F1 scores of 0.955 and 0.945, respectively;3) We encoded the extracted entities into standardized concepts and enriched the baseline dictionary using these entities. In this study, a customized NLP tool was developed and validated for extracting acupuncture point location terms. This tool can be used in various informatics applications to support acupuncture research, education, and practices. © 2023 IEEE.

关键词： Acupuncture

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Assessing the Mental Health Impact of COVID-19 on the US Population: A Large-Scale Survey Analysis Using SMOTE 24

Assessing the Mental Health Impact of COVID-19 on the US Pop...

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8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Rayguru, Chinmayee Su, Emily Chia-Yu Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University 250 Wu-Xing Street Taipei11031 Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei11031 Taiwan

ISBN: (纸本)9798400716874

The coronavirus (COVID-19) outbreak, recognized as one of the deadliest health crises in recent history, swiftly affected over 200 countries. The pandemic has posed complex challenges, specifically affected not only the rising number of cases but also deeply influenced individual mental health. This research explores the significant mental health implications of the COVID-19 pandemic on the US population, analyzed through a large-scale survey of 25,136 participants across various ages, economic backgrounds, and chronic disease status. We categorized mental health status into three risk levels: low, moderate, and high, based on the key features influencing stress levels. Notably, our findings reveal that the age group 25-54 years exhibited higher anxiety levels compared to other age groups. The implementation of Extreme Gradient Boosting (XGBoost) with Synthetic Minority Over-sampling (SMOTE) Technique for balancing data yielded impressive accuracy rates: 94.55% for high risk, 90.73% for moderate risk, and 77.77% for low risk, respectively. These results significantly outperformed the Random Forest (RF) model in both imbalanced and SMOTE balanced datasets. Furthermore, the study identified high obesity and chronic diseases, such as bronchitis, as factors exacerbating stress levels. This research contributes valuable insights to the mental health condition prediction during COVID-19 pandemic by underlining the importance of targeted interventions for high-risk groups. © 2024 Copyright ACM.

关键词： COVID-19

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Protein tyrosine phosphatases:emerging role in cancer therapy resistance

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cancer Communications 2024年第6期44卷 637-653页

作者： Min Zhao Wen Shuai Zehao Su Ping Xu Aoxue Wang Qiu Sun Guan Wang Innovation Center of Nursing Research Nursing Key Laboratory of Sichuan ProvinceDepartment of BiotherapyCancer Center and State Key Laboratory of BiotherapyNational Clinical Research Center for GeriatricsWest China HospitalWest China School of NursingSichuan UniversityChengduSichuanP.R.China West China Biomedical Big Data Center Med-X Center for InformaticsSichuan UniversityChengduSichuanP.R.China Emergency Department Zigong Fourth People’s HospitalChengduSichuanP.R.China

Background:Tyrosine phosphorylation of intracellular proteins is a posttranslational modification that plays a regulatory role in signal transduction during cellular *** of signal transduction proteins caused by protein tyrosine phosphatases(PTPs)contributed their role as a convergent node to mediate cross-talk between signaling *** the context of cancer,PTP-mediated pathways have been identified as signaling hubs that enabled cancer cells to mitigate stress induced by clinical *** is achieved by the promotion of constitutive activation of growth-stimulatory signaling pathways or modulation of the immune-suppressive tumor *** evidences suggested that anticancer drugs will release their greatest therapeutic potency when combined with PTP inhibitors,reversing drug resistance that was responsible for clinical failures during cancer *** covered:This review aimed to elaborate recent insights that supported the involvement of PTP-mediated pathways in the development of resistance to targeted therapy and immune-checkpoint *** opinion:This review proposed the notion of PTP inhibition in anticancer combination therapy as a potential strategy in clinic to achieve long-term tumor *** clinical trials are currently underway to assess the safety and efficacy of combination therapy in advanced-stage tumors.

关键词： cancer treatment combination therapy drug resistance protein tyrosine phosphatase

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First-line penpulimab(an anti-PD1 antibody)and anlotinib(an angiogenesis inhibitor)with nab-paclitaxel/gemcitabine(PAAG)in metastatic pancreatic cancer:a prospective,multicentre,biomolecular exploratory,phase II trial

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Signal Transduction and Targeted Therapy 2024年第7期9卷 2960-2969页

作者： Huizi Sha Fan Tong Jiayao Ni Yi Sun Yahui Zhu Liang Qi Xiaoqin Li Wei Li Yan Yang Qing Gu Xing Zhang Xiaoxuan Wang Chan Zhu Dongsheng Chen Baorui Liu Juan Du The Comprehensive Cancer Center Nanjing Drum Tower HospitalAffiliated Hospital of Medical SchoolNanjing University&Clinical Cancer Institute of Nanjing UniversityNanjingChina The Comprehensive Cancer Center Nanjing Drum Tower HospitalClinical College of Traditional Chinese and Western MedicineNanjing University of Chinese MedicineNanjingChina Department of Oncology The Affiliated Hospital of Jiangsu UniversityZhenjiangChina Department of Oncology The First Affiliated Hospital of Soochow UniversitySuzhouChina Department of Oncology The Affiliated Jiangning Hospital of Nanjing Medical UniversityNanjingChina National Institute of Healthcare Data Science at Nanjing University NanjingChina State Key Laboratory of Neurology and Oncology Drug Development Jiangsu Simcere Diagnostics Co.Ltd.Nanjing Simcere Medical Laboratory Science Co.Ltd.NanjingChina

Metastatic pancreatic cancer(mPC)has a dismal ***,we conducted a prospective,multicentre,single-arm,phase II trial evaluating the efficacy and safety of penpulimab and anlotinib in combination with nab-paclitaxel/gemcitabine(PAAG)in patients with first-line mPC(NCT05493995).The primary endpoints included the objective response rate(ORR)and disease control rate(DCR),while secondary endpoints encompassed progression-free survival(PFS),overall survival(OS),and *** 66 patients analysed for efficacy,the best response,indicated by the ORR,was recorded at 50.0%(33/66)(95%CI,37.4–62.6%),with 33 patients achieving partial response(PR).Notably,the DCR was 95.5%(63/66,95%CI,87.3–99.1%).The median PFS(mPFS)and OS(mOS)were 8.8(95%CI,8.1–11.6),and 13.7(95%CI,12.4 to not reached)months,*** 3/4 treatment-related adverse events(TRAEs)were reported in 39.4%of patients(26/66).In prespecified exploratory analysis,patients with altered SWI/SNF complex had a poorer ***,low serum CA724 level,high T-cell recruitment,low Th17 cell recruitment,and high NK CD56dim cell scores at baseline were potential predicative biomarkers for more favourable *** conclusion,PAAG as a first-line therapy demonstrated tolerability with promising clinical efficacy for *** biomolecular findings identified in this study possess the potential to guide the precise clinical application of the triple-combo regimen.

关键词： CA724 prospective centre

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Features of gastric cancer by anatomic subsite in northern China: A multi-center Health science Report database study

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World Journal of Gastrointestinal Oncology 2022年第11期14卷 2238-2252页

作者： Rui-Ze Qu Yan-Peng Ma Xiao-Yuan Bao Li-Yuan Tao Xin Zhou Si-Yi Lu Yi Zhang Bing-Yan Wang Fei Li Lin Tuo Zhi-Peng Zhang Wei Fu Department of General Surgery Cancer CenterPeking University Third HospitalBeijing 100191China Medical Informatics Center Peking University Health Science CenterBeijing 100191China Research Center of Clinical Epidemiology Peking University Third HospitalBeijing 100191China Department of Hospital Management Peking University Health Science CenterBeijing 100191China

BACKGROUND The features of gastric cancer based on the anatomic site remain unknown in northern China *** To analyze gastric cancer features and associated trends based on the anatomical site in northern China *** This cross-sectional study used incident gastric cancer case data from 10 Peking University-affiliated hospitals(2014 to 2018).The clinical and prevailing local features were *** A total of 10709 patients were enrolled,including antral(42.97%),cardia(34.30%),and stomach body(18.41%)gastric cancer *** in the cardia had the highest male:female ratio,proportion of elderly patients,and patients with complications,including hypertension,diabetes,cerebrovascular,and coronary diseases(P<0.001).gastric cancer involving the antrum showed the lowest proportion of patients from rural areas and accounted for the highest hospitalization rate and cost(each P<0.001).The proportion of patients with cancer involving the cardia increased with an increase in the number of gastroesophageal reflux disease cases during the same period(P<0.001).Multivariate analysis revealed that tumor location in the cardia increased the risk of inhospital mortality(P=0.046).Anatomical subsite was not linked to postoperative *** The features of gastric cancer based on the anatomical site differ between northern China and other regions,both globally and within the *** factors may account for these differences and should affect policy-making and clinical practice.

关键词： Feature Gastric cancer Anatomical site Northern China

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Progress in research on ultrasound radiomics for predicting the prognosis of breast cancer

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cancer Innovation 2023年第4期2卷 283-289页

作者： Xuantong Gong Xuefeng Liu Xiaozheng Xie Yong Wang Department of Ultrasound National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBejjing Advanced Innovation Center for Big Data and Brain Computing(BDBC)Beihang UniversityBeijingChina School of Computer and Communication Engi neering.University of Science and Technology Beijing BeijingChina

Breast cancer is the most common malignant tumor and the leading cause of cancer-related deaths in women *** means of predicting the prognosis of breast cancer are very helpful in guiding treatment and improving patients'*** extracted by radiomics reflect the genetic and molecular characteristics of a tumor and are related to its biological behavior and the patient's ***,radiomics provides a new approach to noninvasive assessment of breast cancer *** is one of the commonest clinical means of examining breast *** recent years,some results of research into ultrasound radiomics for diagnosing breast cancer,predicting lymph node status,treatment response,recurrence and survival times,and other aspects,have been *** this article,we review the current research status and technical challenges of ultrasound radiomics for predicting breast cancer *** aim to provide a reference for radiomics researchers,promote the development of ultrasound radiomics,and advance its clinical application.

关键词： breast cancer deeplearning prognosisprediction radiomics ultrasound

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A Cross-Validated Feature Selection (CVFS) approach for extracting the most parsimonious feature sets and discovering potential antimicrobial resistance (AMR) biomarkers

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Computational and Structural Biotechnology Journal 2023年 21卷 769-779页

作者： Yang, Ming-Ren Wu, Yu-Wei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei110 Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei106 Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei110 Taiwan

Understanding genes and their underlying mechanisms is critical in deciphering how antimicrobial-resistant (AMR) bacteria withstand detrimental effects of antibiotic drugs. At the same time the genes related to AMR phenotypes may also serve as biomarkers for predicting whether a microbial strain is resistant to certain antibiotic drugs. We developed a Cross-Validated Feature Selection (CVFS) approach for robustly selecting the most parsimonious gene sets for predicting AMR activities from bacterial pan-genomes. The core idea behind the CVFS approach is interrogating features among non-overlapping sub-parts of the datasets to ensure the representativeness of the features. By randomly splitting the dataset into disjoint sub-parts, conducting feature selection within each sub-part, and intersecting the features shared by all sub-parts, the CVFS approach is able to achieve the goal of extracting the most representative features for yielding satisfactory AMR activity prediction accuracy. By testing this idea on bacterial pan-genome datasets, we showed that this approach was able to extract the most succinct feature sets that predicted AMR activities very well, indicating the potential of these genes as AMR biomarkers. The functional analysis demonstrated that the CVFS approach was able to extract both known AMR genes and novel ones, suggesting the capabilities of the algorithm in selecting relevant features and highlighting the potential of the novel genes in expanding the antimicrobial resistance gene databases. © 2022 The Author(s)

关键词： Biomarkers

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