Có thể các phương pháp tiếp cận thuật toán học sâu như mô hình khai thác văn bản y sinh học được đào tạo trước trong kho ngữ liệu ngôn ngữ tự nhiên áp dụng cho việc nhận dạng ung thư bằng trí tuệ nhân tạo. Cơ chế nhận dạng của ứng dụng trí tuệ nhân tạo có thể được dịch sang ngôn ngữ của con người thông qua dấu hiệu của sự chú ý. Các viễn cảnh trong tương lai về nhận dạng ung thư trong trí tuệ nhân tạo có thể cần tập trung vào việc dịch trí tuệ nhân tạo và ngôn ngữ của con người. Khả năng sống sót của bệnh nhân ung thư gan có thể được dự đoán với sự tích hợp đa nguyên tố dựa trên thuật toán học sâu. Kiến trúc Autoencoder được sử dụng để tích hợp dữ liệu giải trình tự RNA (RNA-Seq), dữ liệu methyl hóa DNA và dữ liệu giải trình tự microRNA (miRNA-Seq) của ung thư biểu mô tế bào gan trong cơ sở dữ liệu tập bản đồ gen ung thư (TCGA).

Để hiểu rõ hơn Cục Thông tin khoa học và công nghệ quốc gia xin giới thiệu một số bài nghiên cứu đã được xuất bản chính thức và các bài viết được chấp nhận đăng trên những cơ sở dữ liệu học thuật chính thống.

1. Springer

1. Artificial intelligence-assisted interpretation of Ki-67 expression and repeatability in breast cancer
Lina Li, Dandan Han, Yongqiang Yu, Jinze Li, Yueping Liu in Diagnostic Pathology (2022)
https://link.springer.com/content/pdf/10.1186%2Fs13000-022-01196-6.pdf

2. Empowering study of breast cancer data with application of artificial intelligence technology: promises, challenges, and use cases
Maryam Panahiazar, Nolan Chen, Dmytro Lituiev… in Clinical & Experimental Metastasis (2022)
https://link.springer.com/content/pdf/10.1007%2Fs10585-021-10125-8.pdf

3. Utility of artificial intelligence with deep learning of hematoxylin and eosin-stained whole slide images to predict lymph node metastasis in T1 colorectal cancer using endoscopically resected specimens; prediction of lymph node metastasis in T1 colorectal cancer
Joo Hye Song, Yiyu Hong, Eun Ran Kim, Seok-Hyung Kim… in Journal of Gastroenterology (2022)
https://link.springer.com/content/pdf/10.1007%2Fs00535-022-01894-4.pdf

4. Depiction of breast cancers on digital mammograms by artificial intelligence-based computer-assisted diagnosis according to cancer characteristics
Si Eun Lee, Kyunghwa Han, Jung Hyun Yoon, Ji Hyun Youk, Eun-Kyung Kim in European Radiology (2022)
https://link.springer.com/content/pdf/10.1007%2Fs00330-022-08718-2.pdf

5. Improve individual treatment by comparing treatment benefits: cancer artificial intelligence survival analysis system for cervical carcinoma
Jieyi Liang, Tingshan He, Hong Li, Xueqing Guo… in Journal of Translational Medicine (2022)
https://link.springer.com/content/pdf/10.1186%2Fs12967-022-03491-8.pdf

6. Using Occlusion-Based Saliency Maps to Explain an Artificial Intelligence Tool in Lung Cancer Screening: Agreement Between Radiologists, Labels, and Visual Prompts
Ziba Gandomkar, Pek Lan Khong, Amanda Punch, Sarah Lewis in Journal of Digital Imaging (2022)
https://link.springer.com/content/pdf/10.1007%2Fs10278-022-00631-w.pdf

7. Clinical analysis and artificial intelligence survival prediction of serous ovarian cancer based on preoperative circulating leukocytes
Ying Feng, Zhixiang Wang, Ran Cui, Meizhu Xiao, Huiqiao Gao… in Journal of Ovarian Research (2022)
https://link.springer.com/content/pdf/10.1186%2Fs13048-022-00994-2.pdf

8. Impact of artificial intelligence in breast cancer screening with mammography
Lan-Anh Dang, Emmanuel Chazard, Edouard Poncelet, Teodora Serb… in Breast Cancer (2022)
https://link.springer.com/content/pdf/10.1007%2Fs12282-022-01375-9.pdf

9. Analysis of mammograms using artificial intelligence to predict response to neoadjuvant chemotherapy in breast cancer patients: proof of concept
I. Skarping, M. Larsson, D. Förnvik in European Radiology (2022)
https://link.springer.com/content/pdf/10.1007%2Fs00330-021-08306-w.pdf

10. An artificial intelligence method to assess the tumor microenvironment with treatment outcomes for gastric cancer patients after gastrectomy
Tao Chen, Xunjun Li, Qingyi Mao, Yiyun Wang, Hanyi Li… in Journal of Translational Medicine (2022)
https://link.springer.com/content/pdf/10.1186%2Fs12967-022-03298-7.pdf

11. Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer
Vipulkumar Dadhania, Daniel Gonzalez, Mustafa Yousif, Jerome Cheng… in BMC Cancer (2022)
https://link.springer.com/content/pdf/10.1186%2Fs12885-022-09559-4.pdf

12. A Systematic Review of Artificial Intelligence Techniques in Cancer Prediction and Diagnosis
Yogesh Kumar, Surbhi Gupta, Ruchi Singla… in Archives of Computational Methods in Engin… (2022)
https://link.springer.com/content/pdf/10.1007%2Fs11831-021-09648-w.pdf

2. Pubmed

1. Predicting cancer outcomes with radiomics and artificial intelligence in radiology.
Bera K, Braman N, Gupta A, Velcheti V, Madabhushi A.
Nat Rev Clin Oncol. 2022 Feb;19(2):132-146. doi: 10.1038/s41571-021-00560-7. Epub 2021 Oct 18.
PMID: 34663898
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034765/pdf/nihms-1790912.pdf

2. Artificial intelligence in cancer target identification and drug discovery.
You Y, Lai X, Pan Y, Zheng H, Vera J, Liu S, Deng S, Zhang L.
Signal Transduct Target Ther. 2022 May 10;7(1):156. doi: 10.1038/s41392-022-00994-0.
PMID: 35538061
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090746/pdf/41392_2022_Article_994.pdf

3. Mining whole-lung information by artificial intelligence for predicting EGFR genotype and targeted therapy response in lung cancer: a multicohort study.
Wang S, Yu H, Gan Y, Wu Z, Li E, Li X, Cao J, Zhu Y, Wang L, Deng H, Xie M, Wang Y, Ma X, Liu D, Chen B, Tian P, Qiu Z, Xian J, Ren J, Wang K, Wei W, Xie F, Li Z, Wang Q, Xue X, Liu Z, Shi J, Li W, Tian J.
Lancet Digit Health. 2022 May;4(5):e309-e319. doi: 10.1016/S2589-7500(22)00024-3. Epub 2022 Mar 24.
PMID: 35341713
https://www.sciencedirect.com/science/article/pii/S2589750022000243?via%3Dihub

4. Artificial intelligence in the diagnosis and management of colorectal cancer liver metastases.
Rompianesi G, Pegoraro F, Ceresa CD, Montalti R, Troisi RI.
World J Gastroenterol. 2022 Jan 7;28(1):108-122. doi: 10.3748/wjg.v28.i1.108.
PMID: 35125822
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8793013/pdf/WJG-28-108.pdf

5. Artificial intelligence and imaging for risk prediction of pancreatic cancer: a narrative review.
Qureshi TA, Javed S, Sarmadi T, Pandol SJ, Li D.
Chin Clin Oncol. 2022 Feb;11(1):1. doi: 10.21037/cco-21-117. Epub 2022 Feb 9.
PMID: 35144387
https://cco.amegroups.com/article/view/89178/html

6. Artificial intelligence: A promising frontier in bladder cancer diagnosis and outcome prediction.
Borhani S, Borhani R, Kajdacsy-Balla A.
Crit Rev Oncol Hematol. 2022 Mar;171:103601. doi: 10.1016/j.critrevonc.2022.103601. Epub 2022 Jan 19.
PMID: 35065220 Review.
https://www.sciencedirect.com/science/article/pii/S1040842822000257?via%3Dihub

7. Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review.
Jones OT, Matin RN, van der Schaar M, Prathivadi Bhayankaram K, Ranmuthu CKI, Islam MS, Behiyat D, Boscott R, Calanzani N, Emery J, Williams HC, Walter FM.
Lancet Digit Health. 2022 Jun;4(6):e466-e476. doi: 10.1016/S2589-7500(22)00023-1.
PMID: 35623799 Review.
https://www.sciencedirect.com/science/article/pii/S2589750022000231?via%3Dihub

8. Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics.
Liberini V, Laudicella R, Balma M, Nicolotti DG, Buschiazzo A, Grimaldi S, Lorenzon L, Bianchi A, Peano S, Bartolotta TV, Farsad M, Baldari S, Burger IA, Huellner MW, Papaleo A, Deandreis D.
Eur Radiol Exp. 2022 Jun 15;6(1):27. doi: 10.1186/s41747-022-00282-0.
PMID: 35701671
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198151/pdf/41747_2022_Article_282.pdf

9. Applications of Artificial Intelligence in Screening, Diagnosis, Treatment, and Prognosis of Colorectal Cancer.
Qiu H, Ding S, Liu J, Wang L, Wang X.
Curr Oncol. 2022 Mar 7;29(3):1773-1795. doi: 10.3390/curroncol29030146.
PMID: 35323346
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947571/pdf/curroncol-29-00146.pdf

10. Empowering study of breast cancer data with application of artificial intelligence technology: promises, challenges, and use cases.
Panahiazar M, Chen N, Lituiev D, Hadley D.
Clin Exp Metastasis. 2022 Feb;39(1):249-254. doi: 10.1007/s10585-021-10125-8. Epub 2021 Oct 26.
PMID: 34697751
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8967766/pdf/10585_2021_Article_10125.pdf

11. Artificial intelligence and machine learning for early detection and diagnosis of colorectal cancer in sub-Saharan Africa.
Waljee AK, Weinheimer-Haus EM, Abubakar A, Ngugi AK, Siwo GH, Kwakye G, Singal AG, Rao A, Saini SD, Read AJ, Baker JA, Balis U, Opio CK, Zhu J, Saleh MN.
Gut. 2022 Jul;71(7):1259-1265. doi: 10.1136/gutjnl-2022-327211. Epub 2022 Apr 13.
PMID: 35418482 No abstract available.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9177787/pdf/gutjnl-2022-327211.pdf

3. Sciendirect

1. Automated prostate cancer grading and diagnosis system using deep learning-based Yolo object detection algorithm
Expert Systems with Applications12 April 2022Volume 201 (Cover date: 1 September 2022)Article 117148
Mehmet Emin SalmanGözde Çakirsoy Çakarİsmail Hakkı Cedi̇moğlu
https://www.sciencedirect.com/science/article/pii/S0957417422005425/pdfft?md5=14d96e6d3d805611d84e271bf056a2db&pid=1-s2.0-S0957417422005425-main.pdf

2. Lung cancer diagnosis in CT images based on Alexnet optimized by modified Bowerbird optimization algorithm
Biomedical Signal Processing and Control10 May 2022Volume 77 (Cover date: August 2022)Article 103791
Yeguo XuYuhang WangNavid Razmjooy
https://www.sciencedirect.com/science/article/pii/S1746809422003135/pdfft?md5=111ba59319b7a223285d5f2ad3593c55&pid=1-s2.0-S1746809422003135-main.pdf

3. A retrospective validation of CanAssist Breast in European early-stage breast cancer patient cohort
The Breast22 February 2022Volume 63 (Cover date: June 2022)Pages 1-8
Aparna GundaChetana BasavarajManjiri M Bakre
https://www.sciencedirect.com/science/article/pii/S0960977622000376/pdfft?md5=69ab072266cde65d56837ce18bcfcd51&pid=1-s2.0-S0960977622000376-main.pdf

4. Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis
The Lancet Digital Health21 June 2022Volume 4, Issue 7 (Cover date: July 2022)Pages e507-e519
Christian LeibigMoritz BrehmerLale Umutlu
https://www.sciencedirect.com/science/article/pii/S258975002200070X/pdfft?md5=9089b08b756df3f89c4d7f26d382a7ed&pid=1-s2.0-S258975002200070X-main.pdf

5. A Novel Breast Cancer Diagnosis Scheme With Intelligent Feature and Parameter Selections
Computer Methods and Programs in Biomedicine20 September 2021Volume 214 (Cover date: February 2022)Article 106432
S. PunithaThompson StephanAmir H. Gandomi
https://www.sciencedirect.com/science/article/pii/S016926072100506X/pdfft?md5=48476bd3f1913d52cf443c38a4f740fd&pid=1-s2.0-S016926072100506X-main.pdf

6. Tumor burden of lung metastases at initial staging in breast cancer patients detected by artificial intelligence as a prognostic tool for precision medicine
Heliyon 15 February 2022 Volume 8, Issue 2 (Cover date: February 2022) Article e08962
Madison R. Kocher, Jordan Chamberlin, Jeremy R. Burt
https://www.sciencedirect.com/science/article/pii/S240584402200250X/pdfft?md5=ba23fe6b04f4c7ca11e72b04fadd3c9d&pid=1-s2.0-S240584402200250X-main.pdf
7. Triboelectric nanogenerator and artificial intelligence to promote precision medicine for cancer
Nano Energy 26 November 2021 Volume 92 (Cover date: February 2022) Article 106783
Meihua Chen, Yuankai Zhou, Yan Zhang
https://www.sciencedirect.com/science/article/pii/S2211285521010326/pdfft?md5=aae7cb98625254b907046270c799649c&pid=1-s2.0-S2211285521010326-main.pdf
8. Analyzing the impact of machine learning and artificial intelligence and its effect on management of lung cancer detection in covid-19 pandemic
Materials Today: Proceedings 3 December 2021 Volume 56, Part 4 (Cover date: 2022) Pages 2213-2216
Raja Sarath Kumar Boddu, Partha Karmakar, Sumanta Bhattacharya
https://www.sciencedirect.com/science/article/pii/S2214785321075714/pdfft?md5=0b06fbd6965f44c51c574f7518df35b3&pid=1-s2.0-S2214785321075714-main.pdf

9. Artificial intelligence: A promising frontier in bladder cancer diagnosis and outcome prediction
Critical Reviews in Oncology/Hematology 19 January 2022 Volume 171 (Cover date: March 2022) Article 103601
Soheila Borhani, Reza Borhani, Andre Kajdacsy-Balla
https://www.sciencedirect.com/science/article/pii/S1040842822000257/pdfft?md5=9b78a7a22e115f7a7682c2bb1ecf9df5&pid=1-s2.0-S1040842822000257-main.pdf

10. Artificial intelligence–powered programmed death ligand 1 analyser reduces interobserver variation in tumour proportion score for non–small cell lung cancer with better prediction of immunotherapy response
European Journal of Cancer 14 May 2022 Volume 170 (Cover date: July 2022) Pages 17-26
Sangjoon Choi, Soo Ick Cho, Seokhwi Kim
https://www.sciencedirect.com/science/article/pii/S0959804922002155/pdfft?md5=f8a21b9b2ff291c86a50b70fe354c1fb&pid=1-s2.0-S0959804922002155-main.pdf

11. Artificial intelligence for detection of microsatellite instability in colorectal cancer—a multicentric analysis of a pre-screening tool for clinical application
ESMO Open 2 March 2022 Volume 7, Issue 2 (Cover date: April 2022) Article 100400
A. Echle, N. Ghaffari Laleh, J. N. Kather
https://www.sciencedirect.com/science/article/pii/S2059702922000217/pdfft?md5=9900087fa8ba0f57e32dbe0183e91f87&pid=1-s2.0-S2059702922000217-main.pdf

12. Network biology and artificial intelligence drive the understanding of the multidrug resistance phenotype in cancer
Drug Resistance Updates 28 January 2022 Volume 60 (Cover date: January 2022) Article 100811
Beatriz Bueschbell, Ana Beatriz Caniceiro, Irina S. Moreira
https://www.sciencedirect.com/science/article/pii/S1368764622000103/pdfft?md5=36531eb2bd4aaee88420ddb77d7c3b32&pid=1-s2.0-S1368764622000103-main.pdf

13. Classification of human skin cancer using Stokes-Mueller decomposition method and artificial intelligence models
Optik 30 October 2021 Volume 249 (Cover date: January 2022) Article 168239
Thanh-Ngan Luu, Quoc-Hung Phan, Thi-Thu-Hien Pham
https://www.sciencedirect.com/science/article/pii/S0030402621017642/pdfft?md5=b48d6fb3948ef8f7b2c70b3271c8e76f&pid=1-s2.0-S0030402621017642-main.pdf

14. Artificial Intelligence–based Detection of FGFR3 Mutational Status Directly from Routine Histology in Bladder Cancer: A Possible Preselection for Molecular Testing?
European Urology Focus 22 April 2021 Volume 8, Issue 2 (Cover date: March 2022) Pages 472-479
Chiara Maria Lavinia Loeffler, Nadina Ortiz Bruechle, Jakob N. Kather
https://www.sciencedirect.com/science/article/pii/S2405456921001139/pdfft?md5=3ff220c8b418d4a9d47d27544bc08c9e&pid=1-s2.0-S2405456921001139-main.pdf

15. Artificial Intelligence in Magnetic Resonance Imaging–based Prostate Cancer Diagnosis: Where Do We Stand in 2021?
European Urology Focus 25 March 2021 Volume 8, Issue 2 (Cover date: March 2022) Pages 409-417
Rodrigo Suarez-Ibarrola, August Sigle, Christian Gratzke
https://www.sciencedirect.com/science/article/pii/S2405456921000997/pdfft?md5=58890f0f805ae2c2a532c7906bd5d5ad&pid=1-s2.0-S2405456921000997-main.pdf

16. Artificial intelligence for breast cancer analysis: Trends & directions
Computers in Biology and Medicine 6 January 2022 Volume 142 (Cover date: March 2022) Article 105221
Shahid Munir Shah, Rizwan Ahmed Khan, Unaiza Sajid
https://www.sciencedirect.com/science/article/pii/S0010482522000130/pdfft?md5=cbf75f9fd0d7d800537d7139b5d7b8ae&pid=1-s2.0-S0010482522000130-main.pdf

17. Emerging artificial intelligence methods for fighting lung cancer: A survey
Clinical eHealth 10 April 2022 Volume 5 (Cover date: December 2022) Pages 19-34
Jieli Zhou, Hongyi Xin
https://www.sciencedirect.com/science/article/pii/S2588914122000119/pdfft?md5=0894d8f224ef6121ffb0ef3a06ce63a7&pid=1-s2.0-S2588914122000119-main.pdf

18. [18F]FDG-PET/CT radiomics and artificial intelligence in lung cancer: Technical aspects and potential clinical applications
Seminars in Nuclear Medicine Available online 15 June 2022 In press, corrected proof
Reyhaneh Manafi-Farid, Emran Askari, Mohsen Beheshti
https://www.sciencedirect.com/science/article/pii/S0001299822000356/pdfft?md5=0e84d7a8a8554905a84dd80452212b4c&pid=1-s2.0-S0001299822000356-main.pdf

19. Diagnosis of breast cancer for modern mammography using artificial intelligence
Mathematics and Computers in Simulation 6 June 2022 Volume 202 (Cover date: December 2022) Pages 316-330
R. Karthiga, K. Narasimhan, Rengarajan Amirtharajan
https://www.sciencedirect.com/science/article/pii/S0378475422002506/pdfft?md5=c414c6bb1e5352124abfdf0fce1989d3&pid=1-s2.0-S0378475422002506-main.pdf

20. UK National Screening Committee's approach to reviewing evidence on artificial intelligence in breast cancer screening
The Lancet Digital Health 21 June 2022 Volume 4, Issue 7 (Cover date: July 2022) Pages e558-e565
Sian Taylor-Phillips, Farah Seedat, Robert J Steele
https://www.sciencedirect.com/science/article/pii/S2589750022000887/pdfft?md5=d59595c2c3f456737a50e8518158cf6f&pid=1-s2.0-S2589750022000887-main.pdf

21. Artificial intelligence recognition of pathological T stage and tumor invasion in rectal cancer based on large panoramic pathological sections
Intelligent Medicine Available online 29 March 2022 In press, corrected proof
Yiheng Ju, Longbo Zheng, Yun Lu
https://www.sciencedirect.com/science/article/pii/S2667102622000109/pdfft?md5=86b599ef05e61c30eaa22298216678a0&pid=1-s2.0-S2667102622000109-main.pdf

22. Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review
The Lancet Digital Health 24 May 2022 Volume 4, Issue 6 (Cover date: June 2022) Pages e466-e476
O T Jones, R N Matin, F M Walter
https://www.sciencedirect.com/science/article/pii/S2589750022000231/pdfft?md5=894da855a6d556746f0d14111fc48de5&pid=1-s2.0-S2589750022000231-main.pdf

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Theo Cục Thông tin khoa học và công nghệ quốc gia, 29/7/2022