I searched PubMed for two phrases, "digital pathology" "artificial intelligence."
I filtered for "open access."
Here are the first 50 results, as of 7/21/2023.
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Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders.
Gedefaw L, Liu CF, Ip RKL, Tse HF, Yeung MHY, Yip SP, Huang CL.
Cells. 2023 Jun 30;12(13):1755. doi: 10.3390/cells12131755.
PMID: 37443789 Free PMC article. Review.
Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the development of computational programs that can mimic human intelligence. In particular, machine learning and deep learning models have enabled the identification an …
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Department Wide Validation in Digital Pathology-Experience from an Academic Teaching Hospital Using the UK Royal College of Pathologists' Guidance.
Kelleher M, Colling R, Browning L, Roskell D, Roberts-Gant S, Shah KA, Hemsworth H, White K, Rees G, Dolton M, Soares MF, Verrill C.
Diagnostics (Basel). 2023 Jun 22;13(13):2144. doi: 10.3390/diagnostics13132144.
PMID: 37443538 Free PMC article.
AIM: we describe our experience of validating departmental pathologists for digital pathology reporting, based on the UK Royal College of Pathologists (RCPath) "Best Practice Recommendations for Implementing Digital Pathology (DP)," at a large academic …
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The slow-paced digital evolution of pathology: lights and shadows from a multifaceted board.
Caputo A, L'Imperio V, Merolla F, Girolami I, Leoni E, Della Mea V, Pagni F, Fraggetta F.
Pathologica. 2023 Jun;115(3):127-136. doi: 10.32074/1591-951X-868.
PMID: 37387439 Free article. Review.
OBJECTIVE: The digital revolution in pathology represents an invaluable resource fto optimise costs, reduce the risk of error and improve patient care, even though it is still adopted in a minority of laboratories. ...To address these challenges and develop a progra …
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Segmentation algorithm can be used for detecting hepatic fibrosis in SD rat.
Hwang JH, Lim M, Han G, Park H, Kim YB, Park J, Jun SY, Lee J, Cho JW.
Lab Anim Res. 2023 Jun 28;39(1):16. doi: 10.1186/s42826-023-00167-2.
PMID: 37381051 Free PMC article.
Therefore, rodent models have been used to examine the histopathological differences between the control and treatment groups to evaluate the efficacy of anti-fibrotic agents in non-clinical research. In addition, with improvements in digital image analysis incorporating …
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Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection.
Carrillo-Perez F, Ortuno FM, Börjesson A, Rojas I, Herrera LJ.
Cancer Imaging. 2023 Jun 26;23(1):66. doi: 10.1186/s40644-023-00586-3.
PMID: 37365659 Free PMC article.
BACKGROUND: Pancreatic ductal carcinoma patients have a really poor prognosis given its difficult early detection and the lack of early symptoms. Digital pathology is routinely used by pathologists to diagnose the disease. However, visually inspecting the tissue is …
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Editorial: Computational pathology for precision diagnosis, treatment, and prognosis of cancer.
Cheng J, Huang K, Xu J.
Front Med (Lausanne). 2023 Jun 6;10:1209666. doi: 10.3389/fmed.2023.1209666. eCollection 2023.
PMID: 37347090 Free PMC article. No abstract available.
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Artificial intelligence in digital pathology of cutaneous lymphomas: A review of the current state and future perspectives.
Doeleman T, Hondelink LM, Vermeer MH, van Dijk MR, Schrader AMR.
Semin Cancer Biol. 2023 Sep;94:81-88. doi: 10.1016/j.semcancer.2023.06.004. Epub 2023 Jun 17.
PMID: 37331571 Free article. Review.
Due to the heterogeneity and rarity of CL, adjunct diagnostic tools are welcomed, especially by pathologists without expertise in this field or with limited access to a centralized specialist panel. The transition into digital pathology workflows enables artifici …
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Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC?
Inamura K, Shigematsu Y.
J Thorac Dis. 2023 May 30;15(5):2882-2884. doi: 10.21037/jtd-22-1862. Epub 2023 Apr 23.
PMID: 37324072 Free PMC article. No abstract available.
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Biobanking in the digital pathology era.
Bonizzi G, Zattoni L, Fusco N.
Oncol Res. 2022 Aug 31;29(4):229-233. doi: 10.32604/or.2022.024892. eCollection 2021.
PMID: 37303941 Free PMC article.
Digital Pathology is becoming more and more important to achieve the goal of precision medicine. Advances in whole-slide imaging, software integration, and the accessibility of storage solutions have changed the pathologists' clinical practice, not only in terms of …
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Corrigendum: Deep learning for the detection of anatomical tissue structures and neoplasms of the skin on scanned histopathological tissue sections.
Kriegsmann K, Lobers F, Zgorzelski C, Kriegsmann J, Janßen C, Meliß RR, Muley T, Sack U, Steinbuss G, Kriegsmann M.
Front Oncol. 2023 May 18;13:1201237. doi: 10.3389/fonc.2023.1201237. eCollection 2023.
PMID: 37274276 Free PMC article.
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Deep learning supported mitoses counting on whole slide images: A pilot study for validating breast cancer grading in the clinical workflow.
van Bergeijk SA, Stathonikos N, Ter Hoeve ND, Lafarge MW, Nguyen TQ, van Diest PJ, Veta M.
J Pathol Inform. 2023 May 4;14:100316. doi: 10.1016/j.jpi.2023.100316. eCollection 2023.
PMID: 37273455 Free PMC article.
This study investigated whether mitoses counting in BC using digital whole slide images (WSI) compares better to light microscopy (LM) when assisted by artificial intelligence (AI), and to which extent differences in digital MC (AI assisted or not) res …
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Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries.
Piya S, Lennerz JK.
Front Med (Lausanne). 2023 May 15;10:1146075. doi: 10.3389/fmed.2023.1146075. eCollection 2023.
PMID: 37256085 Free PMC article.
Digital Pathology (DP) and Artificial Intelligence (AI) can be useful in low- and middle-income countries; however, many challenges exist. ...
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Diagnosis of Liver Fibrosis Using Artificial Intelligence: A Systematic Review.
Popa SL, Ismaiel A, Abenavoli L, Padureanu AM, Dita MO, Bolchis R, Munteanu MA, Brata VD, Pop C, Bosneag A, Dumitrascu DI, Barsan M, David L.
Medicina (Kaunas). 2023 May 21;59(5):992. doi: 10.3390/medicina59050992.
PMID: 37241224 Free PMC article. Review.
Background and Objectives: The development of liver fibrosis as a consequence of continuous inflammation represents a turning point in the evolution of chronic liver diseases. The recent developments of artificial intelligence (AI) applications show a high potential …
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Artificial Intelligence-Based Opportunities in Liver Pathology-A Systematic Review.
Allaume P, Rabilloud N, Turlin B, Bardou-Jacquet E, Loréal O, Calderaro J, Khene ZE, Acosta O, De Crevoisier R, Rioux-Leclercq N, Pecot T, Kammerer-Jacquet SF.
Diagnostics (Basel). 2023 May 19;13(10):1799. doi: 10.3390/diagnostics13101799.
PMID: 37238283 Free PMC article. Review.
BACKGROUND: Artificial Intelligence (AI)-based Deep Neural Networks (DNNs) can handle a wide range of applications in image analysis, ranging from automated segmentation to diagnostic and prediction. ...Hence, DNN models in liver pathology present future oppo …
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Artificial Intelligence in Clinical Oncology: From Data to Digital Pathology and Treatment.
Senthil Kumar K, Miskovic V, Blasiak A, Sundar R, Pedrocchi ALG, Pearson AT, Prelaj A, Ho D.
Am Soc Clin Oncol Educ Book. 2023 May;43:e390084. doi: 10.1200/EDBK_390084.
PMID: 37235822 Free article.
Recently, a wide spectrum of artificial intelligence (AI)-based applications in the broader categories of digital pathology, biomarker development, and treatment have been explored. In the domain of digital pathology, these have included …
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Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images.
Bokhorst JM, Nagtegaal ID, Fraggetta F, Vatrano S, Mesker W, Vieth M, van der Laak J, Ciompi F.
Sci Rep. 2023 May 24;13(1):8398. doi: 10.1038/s41598-023-35491-z.
PMID: 37225743 Free PMC article.
In colorectal cancer (CRC), artificial intelligence (AI) can alleviate the laborious task of characterization and reporting on resected biopsies, including polyps, the numbers of which are increasing as a result of CRC population screening programs ongoing in many c …
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A suggested way forward for adoption of AI-Enabled digital pathology in low resource organizations in the developing world.
Zehra T, Parwani A, Abdul-Ghafar J, Ahmad Z.
Diagn Pathol. 2023 May 18;18(1):68. doi: 10.1186/s13000-023-01352-6.
PMID: 37202805 Free PMC article. Review.
Due to these issues, precious data cannot be saved and utilized properly. However, digital techniques can be adopted even in low resource settings with significant financial constraints. In this review article, we suggest some of the options available to pathologists in de …
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Biased data, biased AI: deep networks predict the acquisition site of TCGA images.
Dehkharghanian T, Bidgoli AA, Riasatian A, Mazaheri P, Campbell CJV, Pantanowitz L, Tizhoosh HR, Rahnamayan S.
Diagn Pathol. 2023 May 17;18(1):67. doi: 10.1186/s13000-023-01355-3.
PMID: 37198691 Free PMC article.
BACKGROUND: Deep learning models applied to healthcare applications including digital pathology have been increasing their scope and importance in recent years. ...It has also been shown that these medically irrelevant patterns can interfere with other applications …
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The promise and challenge of spatial omics in dissecting tumour microenvironment and the role of AI.
Lee RY, Ng CW, Rajapakse MP, Ang N, Yeong JPS, Lau MC.
Front Oncol. 2023 May 1;13:1172314. doi: 10.3389/fonc.2023.1172314. eCollection 2023.
PMID: 37197415 Free PMC article. Review.
In this review, we present state-of-the-art spatial omics technologies, their applications, major strengths, and limitations as well as the role of artificial intelligence (AI) in TME studies....
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3D Visualization, Skeletonization and Branching Analysis of Blood Vessels in Angiogenesis.
Ramakrishnan V, Schönmehl R, Artinger A, Winter L, Böck H, Schreml S, Gürtler F, Daza J, Schmitt VH, Mamilos A, Arbelaez P, Teufel A, Niedermair T, Topolcan O, Karlíková M, Sossalla S, Wiedenroth CB, Rupp M, Brochhausen C.
Int J Mol Sci. 2023 Apr 23;24(9):7714. doi: 10.3390/ijms24097714.
PMID: 37175421 Free PMC article.
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Automated Deep Learning-Based Classification of Wilms Tumor Histopathology.
van der Kamp A, de Bel T, van Alst L, Rutgers J, van den Heuvel-Eibrink MM, Mavinkurve-Groothuis AMC, van der Laak J, de Krijger RR.
Cancers (Basel). 2023 May 8;15(9):2656. doi: 10.3390/cancers15092656.
PMID: 37174121 Free PMC article.
However, due to the heterogeneous nature of the tumor, significant interobserver variation between pathologists in WT diagnosis has been observed, potentially leading to misclassification and suboptimal treatment. We investigated whether artificial intelligence (AI) …
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Value of Artificial Intelligence in Evaluating Lymph Node Metastases.
Caldonazzi N, Rizzo PC, Eccher A, Girolami I, Fanelli GN, Naccarato AG, Bonizzi G, Fusco N, d'Amati G, Scarpa A, Pantanowitz L, Marletta S.
Cancers (Basel). 2023 Apr 26;15(9):2491. doi: 10.3390/cancers15092491.
PMID: 37173958 Free PMC article. Review.
Evaluating lymph nodes for the presence of metastatic cancerous cells can be a lengthy, monotonous, and error-prone process. Owing to digital pathology, artificial intelligence (AI) applied to whole slide images (WSIs) of lymph nodes can be exploited f …
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Eye for an AI: More-than-seeing, fauxtomation, and the enactment of uncertain data in digital pathology.
Carboni C, Wehrens R, van der Veen R, de Bont A.
Soc Stud Sci. 2023 May 8:3063127231167589. doi: 10.1177/03063127231167589. Online ahead of print.
PMID: 37154611 Free article.
Artificial Intelligence (AI) tools are being developed to assist with increasingly complex diagnostic tasks in medicine. ...Sensorial and intra-active uncertainty stem from the ontological otherness of digital objects, materialized in their affordances, and r …
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Privacy risks of whole-slide image sharing in digital pathology.
Holub P, Müller H, Bíl T, Pireddu L, Plass M, Prasser F, Schlünder I, Zatloukal K, Nenutil R, Brázdil T.
Nat Commun. 2023 May 4;14(1):2577. doi: 10.1038/s41467-023-37991-y.
PMID: 37142591 Free PMC article.
Access to large volumes of so-called whole-slide images-high-resolution scans of complete pathological slides-has become a cornerstone of the development of novel artificial intelligence methods in pathology for diagnostic use, education/training of pathologi …
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Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.
Spratt DE, Tang S, Sun Y, Huang HC, Chen E, Mohamad O, Armstrong AJ, Tward JD, Nguyen PL, Lang JM, Zhang J, Mitani A, Simko JP, DeVries S, van der Wal D, Pinckaers H, Monson JM, Campbell HA, Wallace J, Ferguson MJ, Bahary JP, Schaeffer EM, Consortium NPCA, Sandler HM, Tran PT, Rodgers JP, Esteva A, Yamashita R, Feng FY.
Res Sq. 2023 Apr 21:rs.3.rs-2790858. doi: 10.21203/rs.3.rs-2790858/v1. Preprint.
PMID: 37131691 Free PMC article.
However, ADT can negatively impact quality of life and there remain no validated predictive models to guide its use. Methods Digital pathology image and clinical data from pre-treatment prostate tissue from 5,727 patients enrolled on five phase III randomized trials …
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Editorial: Artificial intelligence in digital pathology image analysis.
Liu Y, Liu X, Zhang H, Liu J, Shan C, Guo Y, Gong X, Tang M.
Front Bioinform. 2023 Apr 13;3:1007986. doi: 10.3389/fbinf.2023.1007986. eCollection 2023.
PMID: 37122999 Free PMC article. No abstract available.
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Tumor Cellularity Assessment of Breast Histopathological Slides via Instance Segmentation and Pathomic Features Explainability.
Altini N, Puro E, Taccogna MG, Marino F, De Summa S, Saponaro C, Mattioli E, Zito FA, Bevilacqua V.
Bioengineering (Basel). 2023 Mar 23;10(4):396. doi: 10.3390/bioengineering10040396.
PMID: 37106583 Free PMC article.
The segmentation and classification of cell nuclei are pivotal steps in the pipelines for the analysis of bioimages. Deep learning (DL) approaches are leading the digital pathology field in the context of nuclei detection and classification. ...Afterwards, the SHAP …
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Bridging clinic and wildlife care with AI-powered pan-species computational pathology.
AbdulJabbar K, Castillo SP, Hughes K, Davidson H, Boddy AM, Abegglen LM, Minoli L, Iussich S, Murchison EP, Graham TA, Spiro S, Maley CC, Aresu L, Palmieri C, Yuan Y.
Nat Commun. 2023 Apr 26;14(1):2408. doi: 10.1038/s41467-023-37879-x.
PMID: 37100774 Free PMC article.
The artificial intelligence algorithm achieves high accuracy in measuring immune response through single-cell classification for two transmissible cancers (canine transmissible venereal tumour, 0.94; Tasmanian devil facial tumour disease, 0.88). ...This study provid …
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Current status of machine learning in thyroid cytopathology.
Wong CM, Kezlarian BE, Lin O.
J Pathol Inform. 2023 Apr 1;14:100309. doi: 10.1016/j.jpi.2023.100309. eCollection 2023.
PMID: 37077698 Free PMC article. Review.
The implementation of Digital Pathology has allowed the development of computational Pathology. ...The development of Artificial Intelligence-assisted algorithms using Cytology digital images has been much more limited due to technical ch …
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Digital Histopathology by Infrared Spectroscopic Imaging.
Bhargava R.
Annu Rev Anal Chem (Palo Alto Calif). 2023 Jun 14;16(1):205-230. doi: 10.1146/annurev-anchem-101422-090956. Epub 2023 Apr 17.
PMID: 37068745 Free article. Review.
Combining this novel contrast mechanism in microscopy with the use of artificial intelligence can transform the practice of histopathology, which currently relies largely on human examination of morphologic patterns within stained tissue. ...Second, an overview of d …
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Explainability and causability in digital pathology.
Plass M, Kargl M, Kiehl TR, Regitnig P, Geißler C, Evans T, Zerbe N, Carvalho R, Holzinger A, Müller H.
J Pathol Clin Res. 2023 Jul;9(4):251-260. doi: 10.1002/cjp2.322. Epub 2023 Apr 12.
PMID: 37045794 Free PMC article. Review.
The current move towards digital pathology enables pathologists to use artificial intelligence (AI)-based computer programmes for the advanced analysis of whole slide images. ...This review article aims to provide medical experts with insights on the i …
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Development of an artificial intelligence-derived histologic signature associated with adjuvant gemcitabine treatment outcomes in pancreatic cancer.
Nimgaonkar V, Krishna V, Krishna V, Tiu E, Joshi A, Vrabac D, Bhambhvani H, Smith K, Johansen JS, Makawita S, Musher B, Mehta A, Hendifar A, Wainberg Z, Sohal D, Fountzilas C, Singhi A, Rajpurkar P, Collisson EA.
Cell Rep Med. 2023 Apr 18;4(4):101013. doi: 10.1016/j.xcrm.2023.101013. Epub 2023 Apr 11.
PMID: 37044094 Free PMC article.
Predictive markers of response to therapy are lacking in PDAC despite various histological and transcriptional classification schemes. We report an artificial intelligence (AI) approach to histologic feature examination that extracts a signature predictive of diseas …
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Erratum: Digital pathology - Rising to the challenge.
Frontiers Production Office.
Front Med (Lausanne). 2023 Mar 15;10:1180693. doi: 10.3389/fmed.2023.1180693. eCollection 2023.
PMID: 37007796 Free PMC article.
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Recent Advances in Melanoma Diagnosis and Prognosis Using Machine Learning Methods.
Grossarth S, Mosley D, Madden C, Ike J, Smith I, Huo Y, Wheless L.
Curr Oncol Rep. 2023 Jun;25(6):635-645. doi: 10.1007/s11912-023-01407-3. Epub 2023 Mar 31.
PMID: 37000340 Free PMC article. Review.
PURPOSE OF REVIEW: The purpose was to summarize the current role and state of artificial intelligence and machine learning in the diagnosis and management of melanoma. ...There have been many incremental advances in both melanoma diagnostics and prognostic tools usi …
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Ethical and legal considerations influencing human involvement in the implementation of artificial intelligence in a clinical pathway: A multi-stakeholder perspective.
Redrup Hill E, Mitchell C, Brigden T, Hall A.
Front Digit Health. 2023 Mar 13;5:1139210. doi: 10.3389/fdgth.2023.1139210. eCollection 2023.
PMID: 36999168 Free PMC article.
INTRODUCTION: Ethical and legal factors will have an important bearing on when and whether automation is appropriate in healthcare. There is a developing literature on the ethics of artificial intelligence (AI) in health, including specific legal or regulatory quest …
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Whole Slide Images in Artificial Intelligence Applications in Digital Pathology: Challenges and Pitfalls.
Basak K, Ozyoruk KB, Demir D.
Turk Patoloji Derg. 2023;39(2):101-108. doi: 10.5146/tjpath.2023.01601.
PMID: 36951221 Free article. English.
The use of digitized data in pathology research is rapidly increasing. The whole slide image (WSI) is an indispensable part of the visual examination of slides in digital pathology and artificial intelligence applications; therefore, the acquisi …
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Learning to predict RNA sequence expressions from whole slide images with applications for search and classification.
Alsaafin A, Safarpoor A, Sikaroudi M, Hipp JD, Tizhoosh HR.
Commun Biol. 2023 Mar 22;6(1):304. doi: 10.1038/s42003-023-04583-x.
PMID: 36949169 Free PMC article.
Deep learning methods are widely applied in digital pathology to address clinical challenges such as prognosis and diagnosis. ...We conducted several experiments and achieved better performance and faster convergence in comparison to the state-of-the-art algorithms. …
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Noninferiority of Artificial Intelligence-Assisted Analysis of Ki-67 and Estrogen/Progesterone Receptor in Breast Cancer Routine Diagnostics.
Abele N, Tiemann K, Krech T, Wellmann A, Schaaf C, Länger F, Peters A, Donner A, Keil F, Daifalla K, Mackens M, Mamilos A, Minin E, Krümmelbein M, Krause L, Stark M, Zapf A, Päpper M, Hartmann A, Lang T.
Mod Pathol. 2023 Mar;36(3):100033. doi: 10.1016/j.modpat.2022.100033.
PMID: 36931740 Free article.
Image analysis assistance with artificial intelligence (AI) has become one of the great promises over recent years in pathology, with many scientific studies being published each year. ...A major reason for this is the missing validation of the robustness of …
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Pathologist Validation of a Machine Learning-Derived Feature for Colon Cancer Risk Stratification.
L'Imperio V, Wulczyn E, Plass M, Müller H, Tamini N, Gianotti L, Zucchini N, Reihs R, Corrado GS, Webster DR, Peng LH, Chen PC, Lavitrano M, Liu Y, Steiner DF, Zatloukal K, Pagni F.
JAMA Netw Open. 2023 Mar 1;6(3):e2254891. doi: 10.1001/jamanetworkopen.2022.54891.
PMID: 36917112 Free PMC article.
IMPORTANCE: Identifying new prognostic features in colon cancer has the potential to refine histopathologic review and inform patient care. Although prognostic artificial intelligence systems have recently demonstrated significant risk stratification for several can …
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Artificial intelligence-based multi-class histopathologic classification of kidney neoplasms.
Gondim DD, Al-Obaidy KI, Idrees MT, Eble JN, Cheng L.
J Pathol Inform. 2023 Feb 16;14:100299. doi: 10.1016/j.jpi.2023.100299. eCollection 2023.
PMID: 36915914 Free PMC article.
Artificial intelligence (AI)-based techniques are increasingly being explored as an emerging ancillary technique for improving accuracy and reproducibility of histopathological diagnosis. ...However, it is not clear how an AI-based model designed for multiple subtyp …
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Development of multiple AI pipelines that predict neoadjuvant chemotherapy response of breast cancer using H&E-stained tissues.
Shen B, Saito A, Ueda A, Fujita K, Nagamatsu Y, Hashimoto M, Kobayashi M, Mirza AH, Graf HP, Cosatto E, Hazama S, Nagano H, Sato E, Matsubayashi J, Nagao T, Cheng E, Hoda SA, Ishikawa T, Kuroda M.
J Pathol Clin Res. 2023 May;9(3):182-194. doi: 10.1002/cjp2.314. Epub 2023 Mar 10.
PMID: 36896856 Free PMC article.
However, other than the subtype of breast cancer, no clear factor indicating sensitivity to NAC has been identified. In this study, we attempted to use artificial intelligence (AI) to predict the effect of preoperative chemotherapy from hematoxylin and eosin images …
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Detection of malignancy in whole slide images of endometrial cancer biopsies using artificial intelligence.
Fell C, Mohammadi M, Morrison D, Arandjelović O, Syed S, Konanahalli P, Bell S, Bryson G, Harrison DJ, Harris-Birtill D.
PLoS One. 2023 Mar 8;18(3):e0282577. doi: 10.1371/journal.pone.0282577. eCollection 2023.
PMID: 36888621 Free PMC article.
In this study we use artificial intelligence (AI) to categorise endometrial biopsy whole slide images (WSI) from digital pathology as either "malignant", "other or benign" or "insufficient". An endometrial biopsy is a key step in diagnosis of endometri …
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Artificial Intelligence Enables Quantitative Assessment of Ulcerative Colitis Histology.
Najdawi F, Sucipto K, Mistry P, Hennek S, Jayson CKB, Lin M, Fahy D, Kinsey S, Wapinski I, Beck AH, Resnick MB, Khosla A, Drage MG.
Mod Pathol. 2023 Jun;36(6):100124. doi: 10.1016/j.modpat.2023.100124. Epub 2023 Feb 15.
PMID: 36841434 Free article.
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CD8+ Cell Density Gradient across the Tumor Epithelium-Stromal Interface of Non-Muscle Invasive Papillary Urothelial Carcinoma Predicts Recurrence-Free Survival after BCG Immunotherapy.
Drachneris J, Rasmusson A, Morkunas M, Fabijonavicius M, Cekauskas A, Jankevicius F, Laurinavicius A.
Cancers (Basel). 2023 Feb 14;15(4):1205. doi: 10.3390/cancers15041205.
PMID: 36831546 Free PMC article.
METHODS: Clinical and pathologic data were retrospectively collected from 157 NMIPUC patients treated with BCG immunotherapy after transurethral resection. Whole-slide digital image analysis of CD8 immunohistochemistry slides was used for tissue segmentation, CD8+ cell qua …
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Artificial intelligence-assisted cancer diagnosis improves the efficiency of pathologists in prostatic biopsies.
Eloy C, Marques A, Pinto J, Pinheiro J, Campelos S, Curado M, Vale J, Polónia A.
Virchows Arch. 2023 Mar;482(3):595-604. doi: 10.1007/s00428-023-03518-5. Epub 2023 Feb 21.
PMID: 36809483 Free PMC article.
Paige Prostate is a clinical-grade artificial intelligence tool designed to assist the pathologist in detecting, grading, and quantifying prostate cancer. In this work, a cohort of 105 prostate core needle biopsies (CNBs) was evaluated through digital path …
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Annotating for Artificial Intelligence Applications in Digital Pathology: A Practical Guide for Pathologists and Researchers.
Montezuma D, Oliveira SP, Neto PC, Oliveira D, Monteiro A, Cardoso JS, Macedo-Pinto I.
Mod Pathol. 2023 Apr;36(4):100086. doi: 10.1016/j.modpat.2022.100086. Epub 2023 Jan 11.
PMID: 36788085 Free article.
Training machine learning models for artificial intelligence (AI) applications in pathology often requires extensive annotation by human experts, but there is little guidance on the subject. In this work, we aimed to describe our experience and provide a simp …
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Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer.
Kiemen AL, Damanakis AI, Braxton AM, He J, Laheru D, Fishman EK, Chames P, Pérez CA, Wu PH, Wirtz D, Wood LD, Hruban RH.
Med. 2023 Feb 10;4(2):75-91. doi: 10.1016/j.medj.2022.11.009. Epub 2023 Jan 24.
PMID: 36773599 Free article. Review.
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Fast and label-free automated detection of microsatellite status in early colon cancer using artificial intelligence integrated infrared imaging.
Gerwert K, Schörner S, Großerueschkamp F, Kraeft AL, Schuhmacher D, Sternemann C, Feder IS, Wisser S, Lugnier C, Arnold D, Teschendorf C, Mueller L, Timmesfeld N, Mosig A, Reinacher-Schick A, Tannapfel A.
Eur J Cancer. 2023 Mar;182:122-131. doi: 10.1016/j.ejca.2022.12.026. Epub 2023 Jan 9.
PMID: 36773401 Free article.
Instead, label-free quantum cascade laser (QCL) based infrared (IR) imaging combined with artificial intelligence (AI) may classify MSI/microsatellite stability (MSS) in unstained tissue sections user-independently and tissue preserving. ...The second step classifyi …
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Code-free machine learning for classification of central nervous system histopathology images.
Jungo P, Hewer E.
J Neuropathol Exp Neurol. 2023 Feb 21;82(3):221-230. doi: 10.1093/jnen/nlac131.
PMID: 36734664 Free PMC article.
Machine learning (ML), an application of artificial intelligence, is currently transforming the analysis of biomedical data and specifically of biomedical images including histopathology. ...
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Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E-stained images: achieving state-of-the-art predictive performance with fewer data using Swin Transformer.
Guo B, Li X, Yang M, Jonnagaddala J, Zhang H, Xu XS.
J Pathol Clin Res. 2023 May;9(3):223-235. doi: 10.1002/cjp2.312. Epub 2023 Feb 1.
PMID: 36723384 Free PMC article.
Many artificial intelligence models have been developed to predict clinically relevant biomarkers for colorectal cancer (CRC), including microsatellite instability (MSI). ...
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