Artificial intelligence in cancer diagnosis and therapy / Hamid Khayyam e.a. [editors].

• TeilnehmendeR: Khayyam, Hamid ,
• Place / Publishing House: Basel : : MDPI,, 2023
• Year of Publication: 2023
• Language: English
• Physical Description: 1 online resource

This reprint covers some significant impacts in the recent research in both the private and public sectors of cancer diagnosis and therapy, in which Artificial Intelligence (AI) and Machine Learning are significant. This reprint is also a collection of forty different complex and challenging problems arranged in five groups: AI in prognosis, grading, and prediction, AI in clinical image analysis, AI models for pathological diagnosis, ML and statistical models for molecular cancer diagnostics and genetics, and AI in triage, risk stratification, and screening cancer, which are all focused on using AI in cancer diagnosis and therapy. All the necessary concepts, solutions, methodologies, and references are supplied except for some fundamental knowledge that is well-known in the general fields of AI and cancer diagnosis and therapy. The readers may, therefore, gain the main concepts of each chapter, with as little of a need as possible to refer to the concepts of the other chapters and references. The readers may hence start to read one or more chapters of the book for their own interests.

Table of Contents

About the Editors xi -- Preface to "Artificial Intelligence in Cancer Diagnosis and Therapy" xiii -- Henrik J. Michaely, Giacomo Aringhieri, Dania Cioni and Emanuele Neri -- Current Value of Biparametric Prostate MRI with Machine-Learning or Deep-Learning in the -- Detection, Grading, and Characterization of Prostate Cancer: A Systematic Review -- Reprinted from: Diagnostics 2022, 12, 799, doi:10.3390/diagnostics12040799 1 -- Russell Frood, Matthew Clark, Cathy Burton, Charalampos Tsoumpas, Alejandro F. Frangi, -- Fergus Gleeson, Chirag Patel, et al. -- Discovery of Pre-Treatment FDG PET/CT-Derived Radiomics-Based Models for Predicting -- Outcome in Diffuse Large B-Cell Lymphoma -- Reprinted from: Cancers 2022, 14, 1711, doi:10.3390/cancers14071711 23 -- Stephan Forchhammer, Amar Abu-Ghazaleh, Gisela Metzler, Claus Garbe -- and Thomas Eigentler -- Development of an Image Analysis-Based Prognosis Score Using Google's Teachable Machine -- in Melanoma -- Reprinted from: Cancers 2022, 14, 2243, doi:10.3390/cancers14092243 37 -- Lifeng Xu, Chun Yang, Feng Zhang, Xuan Cheng, Yi Wei, Shixiao Fan, Minghui Liu, et al. -- Deep Learning Using CT Images to Grade Clear Cell Renal Cell Carcinoma: Development and -- Validation of a Prediction Model -- Reprinted from: Cancers 2022, 14, 2574, doi:10.3390/ cancers14112574 49 -- Sara Merkaj, Ryan C. Bahar, Tal Zeevi, MingDe Lin, Ichiro Ikuta, Khaled Bousabarah, -- Gabriel I. Cassinelli Petersen, et al. -- Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: -- Challenges and Opportunities -- Reprinted from: Cancers 2022, 14, 2623, doi:10.3390/cancers14112623 65 -- Qiyi Hu, Guojie Wang, Xiaoyi Song, Jingjing Wan, Man Li, Fan Zhang, Qingling Chen, et al. -- Machine Learning Based on MRI DWI Radiomics Features for Prognostic Prediction in -- Nasopharyngeal Carcinoma -- Reprinted from: Cancers 2022, 14, 3201, doi:10.3390/cancers14133201 81 -- Yuki Ito, Takahiro Nakajima, Terunaga Inage, Takeshi Otsuka, Yuki Sata, Kazuhisa Tanaka, -- Yuichi Sakairi, et al. -- Prediction of Nodal Metastasis in Lung Cancer Using Deep Learning of Endobronchial -- Ultrasound Images -- Reprinted from: Cancers 2022, 14, 3334, doi:10.3390/cancers14143334 93 -- Marco Bertolini, Valeria Trojani, Andrea Botti, Noemi Cucurachi, Marco Galaverni, -- Salvatore Cozzi, Paolo Borghetti, et al. -- Novel Harmonization Method for Multi-Centric Radiomic Studies in Non-Small Cell -- Lung Cancer -- Reprinted from: Curr. Oncol. 2022, 29, 410, doi:10.3390/curroncol29080410 105 -- Wei Zhao, Yingli Sun, Kaiming Kuang, Jiancheng Yang, Ge Li, Bingbing Ni, -- Yingjia Jiang, et al. -- ViSTA: A Novel Network Improving Lung Adenocarcinoma Invasiveness Prediction from -- Follow-Up CT Series -- Reprinted from: Cancers 2022, 14, 3675, doi:10.3390/cancers14153675 121 -- Jason C. Hsu, Phung-Anh Nguyen, Phan Thanh Phuc, Tsai-Chih Lo, Min-Huei Hsu, -- Min-Shu Hsieh, Nguyen Quoc Khanh Le, et al. -- Development and Validation of Novel Deep-Learning Models Using Multiple Data Types for -- Lung Cancer Survival -- Reprinted from: Cancers 2022, 14, 5562, doi:10.3390/cancers14225562 133 -- Shuchita Dhwiren Patel, Andrew Davies, Emma Laing, Huihai Wu, Jeewaka Mendis -- and Derk-Jan Dijk -- Prognostication in Advanced Cancer by Combining Actigraphy-Derived Rest-Activity and -- Sleep Parameters with Routine Clinical Data: An Exploratory Machine Learning Study -- Reprinted from: Cancers 2023, 15, 503, doi:10.3390/cancers15020503 147 -- Bart M. de Vries, Sandeep S. V. Golla, Gerben J. C. Zwezerijnen, Otto S. Hoekstra, -- Yvonne W. S. Jauw, Marc C. Huisman, Guus A. M. S. van Dongen, et al. -- 3D Convolutional Neural Network-Based Denoising of Low-Count Whole-Body -- 18F-Fluorodeoxyglucose and 89Zr-Rituximab PET Scans -- Reprinted from: Diagnostics 2022, 12, 596, doi:10.3390/diagnostics12030596 169 -- Marco Solbiati, Tiziana Ierace, Riccardo Muglia, Vittorio Pedicini, Roberto Iezzi, -- Katia M. Passera, Alessandro C. Rotilio, et al. -- Thermal Ablation of Liver Tumors Guided by Augmented Reality: An Initial -- Clinical Experience -- Reprinted from: Cancers 2022, 14, 1312, doi:10.3390/cancers14051312 183 -- Pavel Alekseevich Lyakhov, Ulyana Alekseevna Lyakhova -- and Nikolay Nikolaevich Nagornov -- System for the Recognizing of Pigmented Skin Lesions with Fusion and Analysis of -- Heterogeneous Data Based on a Multimodal Neural Network -- Reprinted from: Cancers 2022, 14, 1819, doi:10.3390/cancers14071819 197 -- Antonio Melillo, Andrea Chirico, Giuseppe De Pietro, Luigi Gallo, Giuseppe Caggianese, -- Daniela Barone, Michelino De Laurentiis, et al. -- Virtual Reality Rehabilitation Systems for Cancer Survivors: A Narrative Review of -- the Literature -- Reprinted from: Cancers 2022, 14, 3163, doi:10.3390/cancers14133163 223 -- Jesus A. Basurto-Hurtado, Irving A. Cruz-Albarran, Manuel Toledano-Ayala, -- Mario Alberto Ibarra-Manzano, Luis A. Morales-Hernandez and Carlos A. Perez-Ramirez -- Diagnostic Strategies for Breast Cancer Detection: From Image Generation to Classification -- Strategies Using Artificial Intelligence Algorithms -- Reprinted from: Cancers 2022, 14, 3442, doi:10.3390/cancers14143442 239 -- Ji-Sun Kim, Byung Guk Kim and Se Hwan Hwang -- Efficacy of Artificial Intelligence-Assisted Discrimination of Oral Cancerous Lesions from -- Normal Mucosa Based on the Oral Mucosal Image: A Systematic Review and Meta-Analysis -- Reprinted from: Cancers 2022, 14, 3499, doi:10.3390/cancers14143499 263 -- Diana Veiga-Canuto, Leonor Cerd`a-Alberich, Cinta Sanguesa ¨ Nebot, Blanca Mart´ınez -- de las Heras, Ulrike Potschger, ¨ Michela Gabelloni, Jos´e Miguel Carot Sierra, et al. -- Comparative Multicentric Evaluation of Inter-Observer Variability in Manual and Automatic -- Segmentation of Neuroblastic Tumors in Magnetic Resonance Images -- Reprinted from: Cancers 2022, 14, 3648, doi:10.3390/cancers14153648 275 -- JaeYen Song, Soyoung Im, Sung Hak Lee and Hyun-Jong Jang -- Deep Learning-Based Classification of Uterine Cervical and Endometrial Cancer Subtypes from -- Whole-Slide Histopathology Images -- Reprinted from: Diagnostics 2022, 12, 2623, doi:10.3390/diagnostics12112623 291 -- Bahrudeen Shahul Hameed and Uma Maheswari Krishnan -- Artificial Intelligence-Driven Diagnosis of Pancreatic Cancer -- Reprinted from: Cancers 2022, 14, 5382, doi:10.3390/cancers14215382 305 -- Victor I. J. Strijbis, Max Dahele, Oliver J. Gurney-Champion, Gerrit J. Blom, -- Marije R. Vergeer, Berend J. Slotman and Wilko F. A. R. Verbakel -- Deep Learning for Automated Elective Lymph Node Level Segmentation for Head and Neck -- Cancer Radiotherapy -- Reprinted from: Cancers 2022, 14, 5501, doi:10.3390/cancers14225501 327 -- Faicel Chamroukhi, Segolene Brivet, Peter Savadjiev, Mark Coates and Reza Forghani -- DECT-CLUST: Dual-Energy CT Image Clusteringand Application to Head and Neck Squamous -- Cell Carcinoma Segmentation -- Reprinted from: Cancers 2022, 12, 3072, doi:10.3390/diagnostics12123072 345 -- Yinghong Guo, Jiangfeng Wu, Yunlai Wang and Yun Jin -- Development and Validation of an Ultrasound-Based Radiomics Nomogram for Identifying -- HER2 Status in Patients with Breast Carcinoma -- Reprinted from: Diagnostics 2022, 12, 3130, doi:10.3390/diagnostics12123130 367 -- Martina Sollini, Margarita Kirienko, Noemi Gozzi, Alessandro Bruno, Chiara Torrisi, -- Luca Balzarini, Emanuele Voulaz, et al. -- The Development of an Intelligent Agent to Detect and Non-Invasively Characterize Lung -- Lesions on CT Scans: Ready for the "Real World"? -- Reprinted from: Diagnostics 2023, 15, 357, doi:10.3390/cancers15020357 385 -- Jang Yoo, Jaeho Lee, Miju Cheon, Sang-Keun Woo, Myung-Ju Ahn, Hong Ryull Pyo, -- Yong Soo Choi, et al. -- Predictive Value of 18F-FDG PET/CT Using Machine Learning for Pathological Response to -- Neoadjuvant Concurrent Chemoradiotherapy in Patients with Stage III Non-Small Cell -- Lung Cancer -- Reprinted from: Cancers 2022, 14, 1987, doi:10.3390/cancers14081987 399 -- Gi Hwan Kim, Yong Mee Cho, So-Woon Kim, Ja-Min Park, Sun Young Yoon, Gowun Jeong, -- Dong-Myung Shin, et al..

Synaptophysin, CD117, and GATA3 as a Diagnostic Immunohistochemical Panel for Small Cell -- Neuroendocrine Carcinoma of the Urinary Tract -- Reprinted from: Cancers 2022, 14, 2495, doi:10.3390/cancers14102495 411 -- Yulan Zhao, Ting Huang and Pintong Huang -- Integrated Analysis of Tumor Mutation Burden and Immune Infiltrates in -- Hepatocellular Carcinoma -- Reprinted from: Diagnostics 2022, 12, 1918, doi:10.3390/diagnostics12081918 425 -- Qing Li, Ruijie Wang, Zhonglin Xie, Lanbo Zhao, Yiran Wang, Chao Sun, Lu Han, et al. -- Clinically Applicable Pathological Diagnosis System for Cell Clumps in Endometrial Cancer -- Screening via Deep Convolutional Neural Networks -- Reprinted from: Cancers 2022, 14, 4109, doi:10.3390/ cancers14174109 443 -- .Yimin Guo, Ting Lyu, Shuguang Liu, Wei Zhang, Youjian Zhou, Chao Zeng -- and Guangming Wu -- Learn to Estimate Genetic Mutation and Microsatellite Instability with Histopathology H&E -- Slides in Colon Carcinoma -- Reprinted from: Cancers 2022, 14, 4144, doi:10.3390/cancers14174144 455 -- Zhengjie Ou, Wei Mao, Lihua Tan, Yanli Yang, Shuanghuan Liu, Yanan Zhang, Bin Li, et al. -- Prediction of Postoperative Pathologic Risk Factors in Cervical Cancer Patients Treated with -- Radical Hysterectomy by Machine Learning -- Reprinted from: Curr. Oncol. 2022, 29, 755, doi:10.3390/curroncol29120755 471 -- Qian Yao, Wei Hou, Kaiyuan Wu, Yanhua Bai, Mengping Long, Xinting Diao, Ling Jia, et al. -- Using Whole Slide Gray Value Map to Predict HER2 Expression and FISH Status in -- Breast Cancer -- Reprinted from: Cancers 2022, 14, 6233, doi:10.3390/cancers14246233 489 -- Wei Zhang, Weiting Zhang, Xiang Li, Xiaoming Cao, Guoqiang Yang and Hui Zhang -- Predicting Tumor Perineural Invasion Status in High-Grade Prostate Cancer Based on -- a Clinical-Radiomics Model Incorporating T2-Weighted and Diffusion-Weighted Magnetic -- Resonance Images -- Reprinted from: Cancers 2023, 15, 86, doi:10.3390/cancers15010086 503 -- Marco Rossi, Salvatore M. Aspromonte, Frederick J. Kohlhapp, Jenna H. Newman, -- Alex Lemenze, Russell J. Pepe, Samuel M. DeFina, et al. -- Gut Microbial Shifts Indicate Melanoma Presence and Bacterial Interactions in a Murine Model -- Reprinted from: Diagnostics 2022, 12, 958, doi:10.3390/diagnostics12040958 519 -- Ilkka Haapala, Anton Kondratev, Antti Roine, Meri M¨akel¨a, Anton Kontunen, -- Markus Karjalainen, Aki Laakso, et al. -- Method for the Intraoperative Detection of IDH Mutation in Gliomas with Differential Mobility -- Spectrometry -- Reprinted from: Curr. Oncol. 2022, 29, 265, doi:10.3390/curroncol29050265 531 -- Joaquim Carreras, Giovanna Roncador and Rifat Hamoudi -- Artificial Intelligence Predicted Overall Survival and Classified Mature B-Cell Neoplasms Based -- on Immuno-Oncology and Immune Checkpoint Panels -- Reprinted from: Cancers 2022, 14, 5318, doi:10.3390/cancers14215318 539 -- Shihori Tanabe, Sabina Quader, Ryuichi Ono, Horacio Cabral, Kazuhiko Aoyagi, -- Akihiko Hirose, Edward J. Perkins, et al. -- Regulation of Epithelial-Mesenchymal Transition Pathway and Artificial Intelligence-Based -- Modeling for Pathway Activity Prediction -- Reprinted from: Curr. Oncol. 2023, 3, 2, doi:10.3390/ onco3010002 585 -- Ji-Eun Na, Yeong-Chan Lee, Tae-Jun Kim, Hyuk Lee, Hong-Hee Won, -- Yang-Won Min, Byung-Hoon Min, et al. -- Machine Learning Model to Stratify the Risk of Lymph Node Metastasis for Early Gastric -- Cancer: A Single-Center Cohort Study -- Reprinted from: Cancers 2022, 14, 1121, doi:10.3390/cancers14051121 599 -- Jeongmin Lee, Bong Joo Kang, Sung Hun Kim and Ga Eun Park -- Evaluation of Computer-Aided Detection (CAD) in Screening Automated Breast Ultrasound -- Based on Characteristics of CAD Marks and False-Positive Marks -- Reprinted from: Cancers 2022, 12, 583, doi:10.3390/diagnostics12030583 611 -- Sebastian Ziegelmayer, Markus Graf, Marcus Makowski, Joshua Gawlitza and Felix Gassert -- Cost-Effectiveness of Artificial Intelligence Support in Computed Tomography-Based Lung -- Cancer Screening -- Reprinted from: Cancers 2022, 14, 1729, doi:10.3390/cancers14071729 623 -- Nikitha Vobugari, Vikranth Raja, Udhav Sethi, Kejal Gandhi, Kishore Raja -- and Salim R. Surani -- Advancements in Oncology with Artificial Intelligence-A Review Article -- Reprinted from: Cancers 2022, 14, 1349, doi:10.3390/cancers14051349 635.