For: | Zhou LQ, Wang JY, Yu SY, Wu GG, Wei Q, Deng YB, Wu XL, Cui XW, Dietrich CF. Artificial intelligence in medical imaging of the liver. World J Gastroenterol 2019; 25(6): 672-682 [PMID: 30783371 DOI: 10.3748/wjg.v25.i6.672] |
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URL: | https://www.wjgnet.com/1007-9327/full/v25/i6/672.htm |
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Fumitoshi Fukuzawa, Yasutaka Yanagita, Daiki Yokokawa, Shun Uchida, Shiho Yamashita, Yu Li, Kiyoshi Shikino, Tomoko Tsukamoto, Kazutaka Noda, Takanori Uehara, Masatomi Ikusaka. Importance of Patient History in Artificial Intelligence–Assisted Medical Diagnosis: Comparison Study. JMIR Medical Education 2024; 10: e52674 doi: 10.2196/52674
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Xiaofei Fan, Xiaoming Qiao, Zhisheng Wang, Luetao Jiang, Yue Liu, Qingshan Sun, Arpit Bhardwaj. Artificial Intelligence-Based CT Imaging on Diagnosis of Patients with Lumbar Disc Herniation by Scalpel Treatment. Computational Intelligence and Neuroscience 2022; 2022: 1 doi: 10.1155/2022/3688630
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Gökhan Kahraman, Kemal Murat Haberal, Osman Nuri Dilek. Imaging features and management of focal liver lesions. World Journal of Radiology 2024; 16(6): 139-167 doi: 10.4329/wjr.v16.i6.139
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Sudheer Babu, Dodala Anil Kumar, Kotha Siva Krishna. Next Generation of Internet of Things. Lecture Notes in Networks and Systems 2023; 445: 641 doi: 10.1007/978-981-19-1412-6_55
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Daniel Vasile Balaban, Mariana Jinga. Digital histology in celiac disease: A practice changer. Artificial Intelligence in Gastroenterology 2020; 1(1): 1-4 doi: 10.35712/aig.v1.i1.1
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Longfei Ma, Rui Wang, Qiong He, Lijie Huang, Xingyue Wei, Xu Lu, Yanan Du, Jianwen Luo, Hongen Liao. Artificial intelligence-based ultrasound imaging technologies for hepatic diseases. iLIVER 2022; 1(4): 252 doi: 10.1016/j.iliver.2022.11.001
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Rakesh Kumar, Sampurna Panda, Mini Anil, Anshul G., Ambali Pancholi. Communication, Networks and Computing. Communications in Computer and Information Science 2023; 1893: 3 doi: 10.1007/978-3-031-43140-1_2
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Tarik Kivrak, Jagadish Nayak, Mehmet Ali Gelen, Prabal Datta Barua, Mehmet Baygin, Hilal Erken Pamukcu, Sengul Dogan, Turker Tuncer, U. Rajendra Acharya. EfDenseNet: Automated Pulmonary Hypertension Detection Model Based on EfficientNetb0 and DenseNet201 Using CT Images. IEEE Access 2023; 11: 142711 doi: 10.1109/ACCESS.2023.3338228
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Liang Ma, Zhihao Zhu, Shijie Yu, Sidney Moses Amadi, Fei Zhao, Jing Zhang, Zhifei Wang. A high-water retention, self-healing hydrogel thyroid model for surgical training. Materials Today Bio 2024; 29: 101334 doi: 10.1016/j.mtbio.2024.101334
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Aisha Siam, Abdel Rahman Alsaify, Bushra Mohammad, Md. Rafiul Biswas, Hazrat Ali, Zubair Shah. Multimodal deep learning for liver cancer applications: a scoping review. Frontiers in Artificial Intelligence 2023; 6 doi: 10.3389/frai.2023.1247195
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Shouqin Jia, Ying Wang, Wuzhang Wang, Qiang Zhang, Xu Zhang. Value of medical imaging artificial intelligence in the diagnosis and treatment of new coronavirus pneumonia. Expert Systems 2022; 39(3) doi: 10.1111/exsy.12740
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Chun-Li Cao, Qiao-Li Li, Jin Tong, Li-Nan Shi, Wen-Xiao Li, Ya Xu, Jing Cheng, Ting-Ting Du, Jun Li, Xin-Wu Cui. Artificial intelligence in thyroid ultrasound. Frontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1060702
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Brittany E. Levy, Jennifer T. Castle, Alexandr Virodov, Wesley S. Wilt, Cody Bumgardner, Thomas Brim, Erin McAtee, Morgan Schellenberg, Kenji Inaba, Zachary D. Warriner. Artificial intelligence evaluation of focused assessment with sonography in trauma. Journal of Trauma and Acute Care Surgery 2023; 95(5): 706 doi: 10.1097/TA.0000000000004021
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Biaoyang Lin, Yingying Ma, ShengJun Wu. Multi-Omics and Artificial Intelligence-Guided Data Integration in Chronic Liver Disease: Prospects and Challenges for Precision Medicine. OMICS: A Journal of Integrative Biology 2022; 26(8): 415 doi: 10.1089/omi.2022.0079
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Qiuxia Wei, Nengren Tan, Shiyu Xiong, Wanrong Luo, Haiying Xia, Baoming Luo. Deep Learning Methods in Medical Image-Based Hepatocellular Carcinoma Diagnosis: A Systematic Review and Meta-Analysis. Cancers 2023; 15(23): 5701 doi: 10.3390/cancers15235701
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Vincent-Béni Sèna Zossou, Freddy Houéhanou Rodrigue Gnangnon, Olivier Biaou, Florent de Vathaire, Rodrigue S. Allodji, Eugène C. Ezin. Automatic Diagnosis of Hepatocellular Carcinoma and Metastases Based on Computed Tomography Images. Journal of Imaging Informatics in Medicine 2024; doi: 10.1007/s10278-024-01192-w
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Roongruedee Chaiteerakij, Darlene Ariyaskul, Kittipat Kulkraisri, Terapap Apiparakoon, Sasima Sukcharoen, Oracha Chaichuen, Phaiboon Pensuwan, Thodsawit Tiyarattanachai, Rungsun Rerknimitr, Sanparith Marukatat. Artificial intelligence for ultrasonographic detection and diagnosis of hepatocellular carcinoma and cholangiocarcinoma. Scientific Reports 2024; 14(1) doi: 10.1038/s41598-024-71657-z
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Jingchen Ma, Hao Yang, Yen Chou, Jin Yoon, Tavis Allison, Ravikumar Komandur, Jon McDunn, Asba Taneem, Richard K. Do, Lawrence H Schwartz, Binsheng Zhao. Generalizability of lesion detection and segmentation when ScaleNAS is trained on a large multi‐organ dataset and validated in the liver. Medical Physics 2024; doi: 10.1002/mp.17504
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Yueqin Dun, Yu Kong, Jinshan Tang. Efficient Johnson-SB Mixture Model for Segmentation of CT Liver Image. Journal of Healthcare Engineering 2022; 2022: 1 doi: 10.1155/2022/5654424
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Grace Lai‐Hung Wong, Pong‐Chi Yuen, Andy Jinhua Ma, Anthony Wing‐Hung Chan, Howard Ho‐Wai Leung, Vincent Wai‐Sun Wong. Artificial intelligence in prediction of non‐alcoholic fatty liver disease and fibrosis. Journal of Gastroenterology and Hepatology 2021; 36(3): 543 doi: 10.1111/jgh.15385
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Javier Briceño. Artificial intelligence and organ transplantation: challenges and expectations. Current Opinion in Organ Transplantation 2020; 25(4): 393 doi: 10.1097/MOT.0000000000000775
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Kaori Tabata, Mana Hashimoto, Haruka Takahashi, Ziyi Wang, Noriyuki Nagaoka, Toru Hara, Hiroshi Kamioka. A morphometric analysis of the osteocyte canaliculus using applied automatic semantic segmentation by machine learning. Journal of Bone and Mineral Metabolism 2022; 40(4): 571 doi: 10.1007/s00774-022-01321-x
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30 |
Ricardo A. Serrano, Alan M. Smeltz. The Promise of Artificial Intelligence-Assisted Point-of-Care Ultrasonography in Perioperative Care. Journal of Cardiothoracic and Vascular Anesthesia 2024; 38(5): 1244 doi: 10.1053/j.jvca.2024.01.034
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31 |
Manal Makram, Ammar Mohammed. Deep Learning Approach for Hepatic Lesion Detection. 2024 Intelligent Methods, Systems, and Applications (IMSA) 2024; : 312 doi: 10.1109/IMSA61967.2024.10652800
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Kareem Ahmed, Mai A. Gad, Amal Elsayed Aboutabl. Performance evaluation of salient object detection techniques. Multimedia Tools and Applications 2022; 81(15): 21741 doi: 10.1007/s11042-022-12567-y
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36 |
Shunsuke Koga, Wei Du. Integrating AI in medicine: Lessons from Chat-GPT's limitations in medical imaging. Digestive and Liver Disease 2024; 56(6): 1114 doi: 10.1016/j.dld.2024.02.014
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37 |
Kristoffer Knutsen Wickstrøm, Eirik Agnalt Østmo, Keyur Radiya, Karl Øyvind Mikalsen, Michael Christian Kampffmeyer, Robert Jenssen. A clinically motivated self-supervised approach for content-based image retrieval of CT liver images. Computerized Medical Imaging and Graphics 2023; 107: 102239 doi: 10.1016/j.compmedimag.2023.102239
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38 |
Nizar Alsharif, Mosleh Hmoud Al-Adhaileh, Mohammed Al-Yaari. Accurate Identification of Attention-deficit/Hyperactivity Disorder Using Machine Learning Approaches. Journal of Disability Research 2024; 3(1) doi: 10.57197/JDR-2023-0053
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39 |
Emerson Nithiyaraj E, Arivazhagan Selvaraj. Morph-Rec: A Novel Computer-Aided Liver Segmentation Model based on Morphological Reconstruction Operation. IETE Journal of Research 2024; 70(3): 2949 doi: 10.1080/03772063.2023.2175052
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40 |
Tsai-Chun Chung, Ya-Hsin Hsu, Tianle Chen, Yang Li, Haochen Yang, Jin-Xiu Yu, I-Chi Lee, Ping-Shan Lai, Yi-Chen Ethan Li, Po-Yen Chen. Machine Learning Integrated Workflow for Predicting Schwann Cell Viability on Conductive MXene Biointerfaces. ACS Applied Materials & Interfaces 2023; 15(39): 46460 doi: 10.1021/acsami.3c08070
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41 |
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Priyanka Arora, Manaswini Behera, Shubhini A. Saraf, Rahul Shukla. Leveraging Artificial Intelligence for Synergies in Drug Discovery: From Computers to Clinics. Current Pharmaceutical Design 2024; 30(28): 2187 doi: 10.2174/0113816128308066240529121148
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Mohammed Yusuf Ansari, Yin Yang, Pramod Kumar Meher, Sarada Prasad Dakua. Dense-PSP-UNet: A neural network for fast inference liver ultrasound segmentation. Computers in Biology and Medicine 2023; 153: 106478 doi: 10.1016/j.compbiomed.2022.106478
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Rakesh Kumar, Mini Anil, Sampurna Panda, Ashish Raj. Medical imaging: Challenges and future directions in AI-Based systems. RECENT ADVANCES IN SCIENCES, ENGINEERING, INFORMATION TECHNOLOGY & MANAGEMENT 2023; 2782: 020147 doi: 10.1063/5.0154355
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Shuli Tang, Tiantian Fan, Xinxin Wang, Can Yu, Chunhui Zhang, Yang Zhou. Cancer Immunotherapy and Medical Imaging Research Trends from 2003 to 2023: A Bibliometric Analysis. Journal of Multidisciplinary Healthcare 2024; : 2105 doi: 10.2147/JMDH.S457367
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Zeliha Demir-Kaymak, Zekiye Turan, Nazli Unlu-Bidik, Semiha Unkazan. Effects of midwifery and nursing students' readiness about medical Artificial intelligence on Artificial intelligence anxiety. Nurse Education in Practice 2024; 78: 103994 doi: 10.1016/j.nepr.2024.103994
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Ashok Kamalanathan, Babu Muthu, Patheri Kuniyil Kaleena. Marvels of Artificial and Computational Intelligence in Life Sciences. 2023; : 62 doi: 10.2174/9789815136807123010009
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Lanping Wu, Bin Dong, Xiaoqing Liu, Wenjing Hong, Lijun Chen, Kunlun Gao, Qiuyang Sheng, Yizhou Yu, Liebin Zhao, Yuqi Zhang. Standard Echocardiographic View Recognition in Diagnosis of Congenital Heart Defects in Children Using Deep Learning Based on Knowledge Distillation. Frontiers in Pediatrics 2022; 9 doi: 10.3389/fped.2021.770182
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Anita Aminoshariae, Ali Nosrat, Venkateshbabu Nagendrababu, Omid Dianat, Hossein Mohammad-Rahimi, Abbey W. O'Keefe, Frank C. Setzer. Artificial Intelligence in Endodontic Education. Journal of Endodontics 2024; 50(5): 562 doi: 10.1016/j.joen.2024.02.011
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Soo Yun Choi, Sunggyun Park, Minchul Kim, Jongchan Park, Ye Ra Choi, Kwang Nam Jin. Evaluation of a deep learning-based computer-aided detection algorithm on chest radiographs. Medicine 2021; 100(16): e25663 doi: 10.1097/MD.0000000000025663
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Chen Chen, Cheng Chen, Mingrui Ma, Xiaojian Ma, Xiaoyi Lv, Xiaogang Dong, Ziwei Yan, Min Zhu, Jiajia Chen. Classification of multi-differentiated liver cancer pathological images based on deep learning attention mechanism. BMC Medical Informatics and Decision Making 2022; 22(1) doi: 10.1186/s12911-022-01919-1
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Zhongyu Yuan, Jiaxuan Peng, Zhenyu Shu, Xue Qin, Jianguo Zhong. Interpretable multitemporal liver function indicator model for prediction and risk factor analysis of drug induced liver injury. Scientific Reports 2024; 14(1) doi: 10.1038/s41598-024-66952-8
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Xim Bokhimi. Learning the Use of Artificial Intelligence in Heterogeneous Catalysis. Frontiers in Chemical Engineering 2021; 3 doi: 10.3389/fceng.2021.740270
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K. Sinha, Z. Uddin, H.I. Kawsar, S. Islam, M.J. Deen, M.M.R. Howlader. Analyzing chronic disease biomarkers using electrochemical sensors and artificial neural networks. TrAC Trends in Analytical Chemistry 2023; 158: 116861 doi: 10.1016/j.trac.2022.116861
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Dan Liu, Fei Liu, Xiaoyan Xie, Liya Su, Ming Liu, Xiaohua Xie, Ming Kuang, Guangliang Huang, Yuqi Wang, Hui Zhou, Kun Wang, Manxia Lin, Jie Tian. Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound. European Radiology 2020; 30(4): 2365 doi: 10.1007/s00330-019-06553-6
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Almir Badnjević, Halida Avdihodžić, Lejla Gurbeta Pokvić. Artificial Intelligence in Medical Devices: Past, Present and Future. Science, Art and Religion 2022; 1(1-2): 101 doi: 10.5005/sar-1-1-2-101
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M. S. Parinitha, Vidya Gowdappa Doddawad, Sowmya Halasabalu Kalgeri, Samyuka S. Gowda, Sahana Patil. Impact of Artificial Intelligence in Endodontics: Precision, Predictions, and Prospects. Journal of Medical Signals & Sensors 2024; 14(9) doi: 10.4103/jmss.jmss_7_24
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Wei Liu, Xue Liu, Mei Peng, Gong-Quan Chen, Peng-Hua Liu, Xin-Wu Cui, Fan Jiang, Christoph F Dietrich. Artificial intelligence for hepatitis evaluation. World Journal of Gastroenterology 2021; 27(34): 5715-5726 doi: 10.3748/wjg.v27.i34.5715
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Michihiro Kudou, Toshiyuki Kosuga, Eigo Otsuji. Artificial intelligence in gastrointestinal cancer: Recent advances and future perspectives. Artificial Intelligence in Gastroenterology 2020; 1(4): 71-85 doi: 10.35712/aig.v1.i4.71
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Onur Dogan, Sanju Tiwari, M. A. Jabbar, Shankru Guggari. A systematic review on AI/ML approaches against COVID-19 outbreak. Complex & Intelligent Systems 2021; 7(5): 2655 doi: 10.1007/s40747-021-00424-8
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Abhiyan Bhandari. Revolutionizing Radiology With Artificial Intelligence. Cureus 2024; doi: 10.7759/cureus.72646
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Carl F. Sabottke, Bradley M. Spieler, Ahmed W. Moawad, Khaled M. Elsayes. Artificial Intelligence in Imaging of Chronic Liver Diseases. Magnetic Resonance Imaging Clinics of North America 2021; 29(3): 451 doi: 10.1016/j.mric.2021.05.011
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V. Antony Asir Daniel, Ravi Ramaraj. A novel modified long short term memory architecture for automatic liver disease prediction from patient records. Concurrency and Computation: Practice and Experience 2022; 34(28) doi: 10.1002/cpe.7372
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Tai-Hui Xia, Man Tan, Jing-Hua Li, Jing-Jing Wang, Qing-Qing Wu, De-Xing Kong. Establish a normal fetal lung gestational age grading model and explore the potential value of deep learning algorithms in fetal lung maturity evaluation. Chinese Medical Journal 2021; 134(15): 1828 doi: 10.1097/CM9.0000000000001547
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Kamran Sattar Awaisi, Qiang Ye, Srinivas Sampalli. A Survey of Industrial AIoT: Opportunities, Challenges, and Directions. IEEE Access 2024; 12: 96946 doi: 10.1109/ACCESS.2024.3426279
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Brian J. Thomsen, Michael Ward, Jin Y. Heo, Elizabeth Huynh, Marc A. Ledesma, Jason A. Fuerst, Arathi Vinayak. Computed tomography scan accuracy for the prediction of lobe and division of liver tumors by four board‐certified radiologists. Veterinary Surgery 2024; 53(7): 1313 doi: 10.1111/vsu.14142
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Antonio Lo Mastro, Enrico Grassi, Daniela Berritto, Anna Russo, Alfonso Reginelli, Egidio Guerra, Francesca Grassi, Francesco Boccia. Artificial intelligence in fracture detection on radiographs: a literature review. Japanese Journal of Radiology 2024; doi: 10.1007/s11604-024-01702-4
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Yusuf YILMAZ, Derya UZELLİ YILMAZ, Duygu YILDIRIM, Esra AKIN KORHAN, Derya ÖZER KAYA. Yapay Zeka ve Sağlıkta Yapay Zekanın Kullanımına Yönelik Sağlık Bilimleri Fakültesi Öğrencilerinin Görüşleri. Süleyman Demirel Üniversitesi Sağlık Bilimleri Dergisi 2021; 12(3): 297 doi: 10.22312/sdusbed.950372
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Ping-Hsun Lu, Chih-Chi Chiang, Wei-Hsuan Yu, Min-Chien Yu, Feng-Nan Hwang, Luminita Moraru. Machine Learning-Based Technique for the Severity Classification of Sublingual Varices according to Traditional Chinese Medicine. Computational and Mathematical Methods in Medicine 2022; 2022: 1 doi: 10.1155/2022/3545712
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Shanmugapriya Survarachakan, Pravda Jith Ray Prasad, Rabia Naseem, Javier Pérez de Frutos, Rahul Prasanna Kumar, Thomas Langø, Faouzi Alaya Cheikh, Ole Jakob Elle, Frank Lindseth. Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions. Artificial Intelligence in Medicine 2022; 130: 102331 doi: 10.1016/j.artmed.2022.102331
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Valeria Tonini, Gabriele Vigutto, Riccardo Donati. Liver surgery for colorectal metastasis: New paths and new goals with the help of artificial intelligence. Artificial Intelligence in Gastroenterology 2022; 3(2): 28-35 doi: 10.35712/aig.v3.i2.28
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Aylin Tahmasebi, Shuo Wang, Corinne E. Wessner, Trang Vu, Ji‐Bin Liu, Flemming Forsberg, Jesse Civan, Flavius F. Guglielmo, John R. Eisenbrey. Ultrasound‐Based Machine Learning Approach for Detection of Nonalcoholic Fatty Liver Disease. Journal of Ultrasound in Medicine 2023; 42(8): 1747 doi: 10.1002/jum.16194
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Sergio J Sanabria, Jeremy Dahl, Amir Pirmoazen, Aya Kamaya, Ahmed ElKaffas. Learning steatosis staging with two-dimensional Convolutional Neural Networks: comparison of accuracy of clinical B-mode with a co-registered spectrogram representation of RF Data. 2020 IEEE International Ultrasonics Symposium (IUS) 2020; : 1 doi: 10.1109/IUS46767.2020.9251329
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Rajnish Kumar, Farhat Ullah Khan, Anju Sharma, Izzatdin B.A. Aziz, Nitesh Kumar Poddar. Recent Applications of Artificial Intelligence in the Detection of Gastrointestinal, Hepatic and Pancreatic Diseases. Current Medicinal Chemistry 2022; 29(1): 66 doi: 10.2174/0929867328666210405114938
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Xing-Rui Wang, Xi Ma, Liu-Xu Jin, Yan-Jun Gao, Yong-Jie Xue, Jing-Long Li, Wei-Xian Bai, Miao-Fei Han, Qing Zhou, Feng Shi, Jing Wang. Application value of a deep learning method based on a 3D V-Net convolutional neural network in the recognition and segmentation of the auditory ossicles. Frontiers in Neuroinformatics 2022; 16 doi: 10.3389/fninf.2022.937891
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Keith Feldman, Justin Baraboo, Deeyendal Dinakarpandian, Sherwin S. Chan. Machine Learning Algorithm Improves the Prediction of Transplant Hepatic Artery Stenosis or Occlusion. Ultrasound Quarterly 2022; doi: 10.1097/RUQ.0000000000000624
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Uli Fehrenbach, Siyi Xin, Alexander Hartenstein, Timo Alexander Auer, Franziska Dräger, Konrad Froböse, Henning Jann, Martina Mogl, Holger Amthauer, Dominik Geisel, Timm Denecke, Bertram Wiedenmann, Tobias Penzkofer. Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI—A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making. Cancers 2021; 13(11): 2726 doi: 10.3390/cancers13112726
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Nitin Chaubal, Thomas Thomsen, Adnan Kabaalioglu, David Srivastava, Stephanie Simone Rösch, Christoph F. Dietrich. Ultrasound and contrast-enhanced ultrasound (CEUS) in infective liver lesions . Zeitschrift für Gastroenterologie 2021; 59(12): 1309 doi: 10.1055/a-1645-3138
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Chunfeng Zheng, Lei Chen, Jihua Jian, Juan Li, Zhonghui Gao. Efficacy evaluation of interventional therapy for primary liver cancer using magnetic resonance imaging and CT scanning under deep learning and treatment of vasovagal reflex. The Journal of Supercomputing 2021; 77(7): 7535 doi: 10.1007/s11227-020-03539-w
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Gopi Battineni, Getu Gamo Sagaro, Nalini Chinatalapudi, Francesco Amenta. Applications of Machine Learning Predictive Models in the Chronic Disease Diagnosis. Journal of Personalized Medicine 2020; 10(2): 21 doi: 10.3390/jpm10020021
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Tasuku Furube, Masashi Takeuchi, Hirofumi Kawakubo, Yusuke Maeda, Satoru Matsuda, Kazumasa Fukuda, Rieko Nakamura, Motohiko Kato, Naohisa Yahagi, Yuko Kitagawa. Automated artificial intelligence–based phase-recognition system for esophageal endoscopic submucosal dissection (with video). Gastrointestinal Endoscopy 2024; 99(5): 830 doi: 10.1016/j.gie.2023.12.037
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Michel L. Leite, Lorena S. de Loiola Costa, Victor A. Cunha, Victor Kreniski, Mario de Oliveira Braga Filho, Nicolau B. da Cunha, Fabricio F. Costa. Artificial intelligence and the future of life sciences. Drug Discovery Today 2021; 26(11): 2515 doi: 10.1016/j.drudis.2021.07.002
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Muhammad Awais, Mais Al Taie, Caleb S. O’Connor, Austin H. Castelo, Belkacem Acidi, Hop S. Tran Cao, Kristy K. Brock. Enhancing Surgical Guidance: Deep Learning-Based Liver Vessel Segmentation in Real-Time Ultrasound Video Frames. Cancers 2024; 16(21): 3674 doi: 10.3390/cancers16213674
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