語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Multimodal Learning for Clinical Dec...
~
Shekhar, Raj.
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures = 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures/ edited by Tanveer Syeda-Mahmood, Klaus Drechsler, Hayit Greenspan, Anant Madabhushi, Alexandros Karargyris, Marius George Linguraru, Cristina Oyarzun Laura, Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Marius Erdt.
其他題名:
10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings /
其他作者:
Erdt, Marius.
面頁冊數:
XII, 138 p. 4 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Database Management. -
電子資源:
https://doi.org/10.1007/978-3-030-60946-7
ISBN:
9783030609467
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures = 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings /
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings /[electronic resource] :edited by Tanveer Syeda-Mahmood, Klaus Drechsler, Hayit Greenspan, Anant Madabhushi, Alexandros Karargyris, Marius George Linguraru, Cristina Oyarzun Laura, Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Marius Erdt. - 1st ed. 2020. - XII, 138 p. 4 illus.online resource. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;12445. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;9219.
CLIP 2020 -- Optimal Targeting Visualizations for Surgical Navigation of Iliosacral Screws -- Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records -- A Radiomics-based Machine Learning Approach to Assess Collateral Circulation in Stroke on Non-contrast Computed Tomography -- Image-based Subthalamic Nucleus Segmentation for Deep Brain Surgery With Electrophysiology Aided Refinement -- 3D Slicer Craniomaxillofacial Modules Support Patient-specific Decision-making for Personalized Healthcare in Dental Research -- Learning Representations of Endoscopic Videos to Detect Tool Presence Without Supervision -- Single-shot Deep Volumetric Regression for Mobile Medical Augmented Reality -- A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge -- Adversarial Prediction of Radiotherapy Treatment Machine Parameters -- ML-CDS 2020 -- Soft Tissue Sarcoma Co-Segmentation in Combined MRI and PET/CT Data -- Towards Automated Diagnosis with Attentive Multi-Modal Learning Using Electronic Health Records and Chest X-rays -- LUCAS: LUng CAncer Screening with Multimodal Biomarkers -- Automatic Breast Lesion Classification by Joint Neural Analysis of Mammography and Ultrasound.
This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.
ISBN: 9783030609467
Standard No.: 10.1007/978-3-030-60946-7doiSubjects--Topical Terms:
669820
Database Management.
LC Class. No.: Q334-342
Dewey Class. No.: 006.3
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures = 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings /
LDR
:03998nam a22004095i 4500
001
1030066
003
DE-He213
005
20201007191305.0
007
cr nn 008mamaa
008
210318s2020 gw | s |||| 0|eng d
020
$a
9783030609467
$9
978-3-030-60946-7
024
7
$a
10.1007/978-3-030-60946-7
$2
doi
035
$a
978-3-030-60946-7
050
4
$a
Q334-342
072
7
$a
UYQ
$2
bicssc
072
7
$a
COM004000
$2
bisacsh
072
7
$a
UYQ
$2
thema
082
0 4
$a
006.3
$2
23
245
1 0
$a
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
$h
[electronic resource] :
$b
10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings /
$c
edited by Tanveer Syeda-Mahmood, Klaus Drechsler, Hayit Greenspan, Anant Madabhushi, Alexandros Karargyris, Marius George Linguraru, Cristina Oyarzun Laura, Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Marius Erdt.
250
$a
1st ed. 2020.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2020.
300
$a
XII, 138 p. 4 illus.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
$v
12445
505
0
$a
CLIP 2020 -- Optimal Targeting Visualizations for Surgical Navigation of Iliosacral Screws -- Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records -- A Radiomics-based Machine Learning Approach to Assess Collateral Circulation in Stroke on Non-contrast Computed Tomography -- Image-based Subthalamic Nucleus Segmentation for Deep Brain Surgery With Electrophysiology Aided Refinement -- 3D Slicer Craniomaxillofacial Modules Support Patient-specific Decision-making for Personalized Healthcare in Dental Research -- Learning Representations of Endoscopic Videos to Detect Tool Presence Without Supervision -- Single-shot Deep Volumetric Regression for Mobile Medical Augmented Reality -- A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge -- Adversarial Prediction of Radiotherapy Treatment Machine Parameters -- ML-CDS 2020 -- Soft Tissue Sarcoma Co-Segmentation in Combined MRI and PET/CT Data -- Towards Automated Diagnosis with Attentive Multi-Modal Learning Using Electronic Health Records and Chest X-rays -- LUCAS: LUng CAncer Screening with Multimodal Biomarkers -- Automatic Breast Lesion Classification by Joint Neural Analysis of Mammography and Ultrasound.
520
$a
This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.
650
2 4
$a
Database Management.
$3
669820
650
2 4
$a
Computational Biology/Bioinformatics.
$3
677363
650
2 4
$a
Computer Appl. in Social and Behavioral Sciences.
$3
669920
650
2 4
$a
Image Processing and Computer Vision.
$3
670819
650
1 4
$a
Artificial Intelligence.
$3
646849
650
0
$a
Database management.
$3
557799
650
0
$a
Bioinformatics.
$3
583857
650
0
$a
Application software.
$3
528147
650
0
$a
Optical data processing.
$3
639187
650
0
$a
Artificial intelligence.
$3
559380
700
1
$a
Erdt, Marius.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1024815
700
1
$a
González Ballester, Miguel Ángel.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1267215
700
1
$a
Wesarg, Stefan.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1267214
700
1
$a
Shekhar, Raj.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1267213
700
1
$a
Oyarzun Laura, Cristina.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1106638
700
1
$a
Linguraru, Marius George.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
891191
700
1
$a
Karargyris, Alexandros.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1326896
700
1
$a
Madabhushi, Anant.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
815885
700
1
$a
Greenspan, Hayit.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
890553
700
1
$a
Drechsler, Klaus.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1075817
700
1
$a
Syeda-Mahmood, Tanveer.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
890554
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783030609450
776
0 8
$i
Printed edition:
$z
9783030609474
830
0
$a
Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
$v
9219
$3
1253644
856
4 0
$u
https://doi.org/10.1007/978-3-030-60946-7
912
$a
ZDB-2-SCS
912
$a
ZDB-2-SXCS
912
$a
ZDB-2-LNC
950
$a
Computer Science (SpringerNature-11645)
950
$a
Computer Science (R0) (SpringerNature-43710)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入