SCI-PUB

AI in Oncology

NEW

Improved accuracy in colorectal cancer tissue decomposition through refinement of established deep learning solutions.

Hematoxylin and eosin-stained biopsy slides are regularly available for colorectal cancer patients...

DOI: 10.1038/s41598-023-42357-x

Prezja F, Äyrämö S, Pölönen I, Ojala T, Lahtinen S, Ruusuvuori P, Kuopio T

Scientific reports, 2023-09-25

NEW

Deep Learning Can Predict Bevacizumab Therapeutic Effect and Microsatellite Instability Directly from Histology in Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) remains a significant cause of mortality among gynecological cancers, with the majority of cases being diagnosed at an advanced stage...

DOI: 10.1016/j.labinv.2023.100247

Wang CW, Lee YC, Lin YJ, Firdi NP, Muzakky H, Liu TC, Lai PJ, Wang CH, Wang YC, Yu MH, Wu CH, Chao TK

Laboratory investigation; a journal of technical methods and pathology, 2023-09-25

Artificial intelligence applied to image-guided radiation therapy (IGRT): a systematic review by the Young Group of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO).

AI and radiomics seem to significantly impact IGRT in all the phases of RT workflow, even if the evidence in the literature is based on retrospective data. Further studies are needed to confirm these tools' potential and provide a stronger correlation with clinical outcomes and gold-standard treatment strategies.

DOI: 10.1007/s11547-023-01708-4

Boldrini L, D'Aviero A, De Felice F, Desideri I, Grassi R, Greco C, Iorio GC, Nardone V, Piras A, Salvestrini V

La Radiologia medica, 2023-09-24

Automated bone marrow cell classification through dual attention gates dense neural networks.

Our data demonstrate that the DAGDNet can improve the efficacy of automatic bone marrow cell classification and can be exploited as an assisting diagnosis tool in clinical applications. Moreover, the DAGDNet is also an efficient model that can swiftly inspect a large number of bone marrow cells and offers the benefit of reducing the probability of an incorrect diagnosis.

DOI: 10.1007/s00432-023-05384-9

Peng K, Peng Y, Liao H, Yang Z, Feng W

Journal of cancer research and clinical oncology, 2023-09-24

Identifying possible hub genes and biological mechanisms shared between bladder cancer and inflammatory bowel disease using machine learning and integrated bioinformatics.

This study explored common gene signatures and the potential pathogenesis of IBD and BC. We revealed that an unbalanced immune response, cell cycle pathway, and neutrophil infiltration might be the common pathogenesis of IBD and BC. Molecular mechanisms for the treatment of IBD and CC still require further investigation.

DOI: 10.1007/s00432-023-05266-0

Liu J, Wu P, Lai S, Wang J, Wang J, Zhang Y

Journal of cancer research and clinical oncology, 2023-09-24

Multiparametric machine learning algorithm for human papillomavirus status and survival prediction in oropharyngeal cancer patients.

Results reinforce artificial intelligence's potential to use tumor imaging and patient characterizations for HPV status and outcome prediction. Utilizing these algorithms can optimize clinical guidance and patient care noninvasively.

DOI: 10.1002/hed.27519

Fazelpour S, Vejdani-Jahromi M, Kaliaev A, Qiu E, Goodman D, Andreu-Arasa VC, Fujima N, Sakai O

Head & neck, 2023-09-24

A novel prediction model of the risk of pancreatic cancer among diabetes patients using multiple clinical data and machine learning.

This study successfully developed a highly accurate 4-year risk model for pancreatic cancer in patients with diabetes using real-world clinical data and multiple machine-learning algorithms. Potentially, our predictors offer an opportunity to identify pancreatic cancer early and thus increase prevention and invention windows to impact survival in diabetic patients.

DOI: 10.1002/cam4.6547

Chen SM, Phuc PT, Nguyen PA, Burton W, Lin SJ, Lin WC, Lu CY, Hsu MH, Cheng CT, Hsu JC

Cancer medicine, 2023-09-23

Survival prediction and prognostic factors in colorectal cancer after curative surgery: insights from cox regression and neural networks.

Medical research frequently relies on Cox regression to analyze the survival distribution of cancer patients...

DOI: 10.1038/s41598-023-42926-0

Alinia S, Asghari-Jafarabadi M, Mahmoudi L, Norouzi S, Safari M, Roshanaei G

Scientific reports, 2023-09-23

Development of artificial intelligence prognostic model for surgically resected non-small cell lung cancer.

There are great expectations for artificial intelligence (AI) in medicine...

DOI: 10.1038/s41598-023-42964-8

Kinoshita F, Takenaka T, Yamashita T, Matsumoto K, Oku Y, Ono Y, Wakasu S, Haratake N, Tagawa T, Nakashima N, Mori M

Scientific reports, 2023-09-23

Staging of colorectal cancer using lipid biomarkers and machine learning.

Our findings demonstrate that correlating multiple disease related features with lipid changes could improve CRC prognosis. The identified signatures could be used as reference biomarkers to predict CRC prognosis and classify stages, and monitor therapeutic intervention.

DOI: 10.1007/s11306-023-02049-z

Krishnan ST, Winkler D, Creek D, Anderson D, Kirana C, Maddern GJ, Fenix K, Hauben E, Rudd D, Voelcker NH

Metabolomics : Official journal of the Metabolomic Society, 2023-09-22

HAHNet: a convolutional neural network for HER2 status classification of breast cancer.

According to our experimental results, the proposed HAHNet achieved high performance in classifying the HER2 status of breast cancer using only H&E stained samples. It can be applied in case classification, benefiting the work of pathologists and potentially helping more breast cancer patients.

DOI: 10.1186/s12859-023-05474-y

Wang J, Zhu X, Chen K, Hao L, Liu Y

BMC bioinformatics, 2023-09-22

Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states.

Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated, and selectively sensitive to immune checkpoint inhibition (ICI)...

DOI: 10.1016/j.xcrm.2023.101189

Nyman J, Denize T, Bakouny Z, Labaki C, Titchen BM, Bi K, Hari SN, Rosenthal J, Mehta N, Jiang B, Sharma B, Felt K, Umeton R, Braun DA, Rodig S, Choueiri TK, Signoretti S, Van Allen EM

Cell reports. Medicine, 2023-09-22

Evaluating Prognostic Value of Dynamics of Circulating Lactate Dehydrogenase in Colorectal Cancer Using Modeling and Machine Learning.

Pre-treatment serum lactate dehydrogenase (LDH) levels have been associated with poor prognosis in several types of cancer, including metastatic colorectal cancer (mCRC)...

DOI: 10.1002/cpt.3052

Ding H, Yuan M, Yang Y, Gupta M, Xu XS

Clinical pharmacology and therapeutics, 2023-09-20

Deep learning to predict lymph node status on pre-operative staging CT in patients with colon cancer.

A deep learning model based on a ResNet-50 framework does not predict LN status on preoperative staging CT in patients with colon cancer.

DOI: 10.1111/1754-9485.13584

Bedrikovetski S, Zhang J, Seow W, Traeger L, Moore JW, Verjans J, Carneiro G, Sammour T

Journal of medical imaging and radiation oncology, 2023-09-21

InDEP: an interpretable machine learning approach to predict cancer driver genes from multi-omics data.

Cancer driver genes are critical in driving tumor cell growth, and precisely identifying these genes is crucial in advancing our understanding of cancer pathogenesis and developing targeted cancer drugs...

DOI: 10.1093/bib/bbad318

Yang H, Liu Y, Yang Y, Li D, Wang Z

Briefings in bioinformatics, 2023-09-23

Evaluation of deep learning-based deliverable VMAT plan generated by prototype software for automated planning for prostate cancer patients.

This study aims to evaluate the dosimetric accuracy of a deep learning (DL)-based deliverable volumetric arc radiation therapy (VMAT) plan generated using DL-based automated planning assistant system (AIVOT, prototype version) for patients with prostate cancer...

DOI: 10.1093/jrr/rrad058

Kadoya N, Kimura Y, Tozuka R, Tanaka S, Arai K, Katsuta Y, Shimizu H, Sugai Y, Yamamoto T, Umezawa R, Jingu K

Journal of radiation research, 2023-09-24

Deep learning integrates histopathology and proteogenomics at a pan-cancer level.

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer...

DOI: 10.1016/j.xcrm.2023.101173

Wang JM, Hong R, Demicco EG, Tan J, Lazcano R, Moreira AL, Li Y, Calinawan A, Razavian N, Schraink T, Gillette MA, Omenn GS, An E, Rodriguez H, Tsirigos A, Ruggles KV, Ding L, Robles AI, Mani DR, Rodland KD, Lazar AJ, Liu W, Fenyö D,

Cell reports. Medicine, 2023-09-22

Use of ChatGPT, GPT-4, and Bard to Improve Readability of ChatGPT's Answers to Common Questions About Lung Cancer and Lung Cancer Screening.

No abstract text is available for this article

DOI: 10.2214/AJR.23.29622

Haver HL, Lin CT, Sirajuddin A, Yi PH, Jeudy J

AJR. American journal of roentgenology, 2023-09-21

Beyond the : Artificial Intelligence Helps Radiologists to Improve Their Performance in Differentiating Colon Carcinoma From Acute Diverticulitis on CT.