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ISMCO 2020: International Symposium on Mathematical and Computational Oncology

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ISMCO
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투고 마감일:
2020-08-31 Extended
통보일:
2020-09-21
개최일:
2020-10-08
개최지:
San Diego, California, USA
개최 횟수:
2
조회: 13506   팔로우: 0   참가: 0

회반 지수 (CP-I)

38.0 / 100
전체 5,687개 중 5,411위 · 상위 96%
학술적 인정 (35%) 데이터 없음 — 중립 기준값 50점으로 계산 —
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산 —
개최 횟수 (20%)
30
커뮤니티 관심도 (10%)
8
공개 자료 충실도 (15%)
25

사용한 입력: 확인되는 개최 횟수: 2 · 지난 24개월 동안 이 페이지를 연 연구자: 2명

공개 자료에서 빠진 항목: 역대 게재율 (+4.5) · 역대 회차 (+3.0) · 최우수 논문 기록 (+2.3)
주최자는 학회를 인증 신청한 뒤 이 페이지에서 바로 추가할 수 있습니다. 점수는 매일 밤 다시 계산됩니다. 이 점수를 올리는 방법

신뢰도 45% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.1 · 산출일 2026-09-25

논문 모집

ISMCO 2020 (International Symposium on Mathematical and Computational Oncology) is an academic conference held in San Diego, California, USA on 2020-10-08. The paper submission deadline is 2020-08-31 (extended). Acceptance notifications are sent on 2020-09-21.

Understanding the origins and growth of cancer requires understanding the role of genetics in encoding proteins that form phenotypes and molecular alterations at multiple levels (e.g., gene, cell, and tissue). Tumors, for example, undergo dynamic spatio-temporal changes, both during their progression and in response to therapies. Therefore, there is a pressing need to design and develop mathematical and computational strategies to harness cancer data in an accurate and efficient fashion. Advanced mathematical and computational models could provide the tools to make therapeutic strategies adaptable enough and to address the emerging targets. Similarly, understanding the interrelationship amongst complex biological processes requires analyzing very large databases of cellular pathways. High-performance computing, big data analytics, data-intensive computing, machine learning, artificial intelligence, and medical image analysis techniques could be critical in addressing these challenges. ISMCO seeks papers describing contributions to the state of the art and practice in mathematical and computational oncology. Topics of interest include, but not limited, the following areas: Topics Multiscale advanced mathematical and computational models Precision medicine and immuno-oncology Spatio-temporal tumor modeling and simulation Tumor forecasting methods Molecular subtyping, survival analysis and prediction Novel experimental cultures Cancer genomics and proteomics Next-generation sequencing and single-cell analysis Systems biology and networks General cancer computational biology Computational methods for anticancer drug development Cancer epidemiology, biomarkers and prevention Statistical methods and data mining for cancer research Deep learning and machine learning for cancer research Big data analytics for cancer research High performance computing for cancer research Data intensive computing for cancer research Scalable and high throughput systems for large-scale cancer-data analytics Text analytics and natural language processing (NLP) for cancer research Automatic semantic annotation of medical content in the context of cancer disease Application of cloud computing, SaaS and PaaS architectures for cancer research Computer-aided diagnosis (CADx) systems for cancer research Computer vision, scientific visualization, and image processing for cancer research Robotics for cancer research
최종 수정: Dou Sun ()

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관련 저널

CCF정식 명칭영향력 지수출판사ISSN
Mathematical Programming2.5Springer0025-5610
Applied Mathematical Modelling5.5Elsevier0307-904X
Mathematical Programming Computation3.6Springer1867-2949
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655

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