Modern Pathology最新文献

{"title":"Introduction to Artificial Intelligence (AI) and Machine Learning (ML) in Pathology & Medicine: Generative & Non-Generative AI Basics.","authors":"Hooman H Rashidi, Joshua Pantanowitz, Mathew Hanna, Ahmad P Tafti, Parth Sanghani, Adam Buchinsky, Brandon Fennell, Mustafa Deebajah, Sarah Wheeler, Thomas Pearce, Ibrahim Abukhiran, Scott Robertson, Octavia Palmer, Mert Gur, Nam K Tran, Liron Pantanowitz","doi":"10.1016/j.modpat.2024.100688","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100688","url":null,"abstract":"<p><p>This manuscript serves as an introduction to a comprehensive seven-part review article series on artificial intelligence (AI) and machine learning (ML) and their current and future influence within pathology and medicine. This introductory review provides a comprehensive grasp of this fast-expanding realm and its potential to transform medical diagnosis, workflow, research, and education. Fundamental terminology employed in AI-ML is covered using an extensive dictionary. The article also provides a broad overview of the main domains in the AI-ML field, encompassing both generative and non-generative (traditional) AI. Thereby serving as a primer to the other six review articles in this series that describe the details about statistics, regulations, bias, ethical dilemmas, and ML-Ops in AI-ML. The intent of these review articles is to better equip individuals who are or will be working in an AI-enabled healthcare system.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100688"},"PeriodicalIF":7.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142927611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular diversity of embryonic-type neuroectodermal tumors arising from testicular germ cell tumors.","authors":"Yang Zong, Rongrong Huang, Mireille Bitar, Alexandra Drakaki, Liying Zhang, Douglas I Lin, Huihui Ye","doi":"10.1016/j.modpat.2024.100702","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100702","url":null,"abstract":"<p><p>Embryonic-type neuroectodermal tumors (ENTs) arising from testicular germ cell tumors (GCTs) is a relatively common type of somatic transformation in GCTs with poor prognosis and limited therapeutic options, particularly when patients develop disease recurrence or metastasis. Knowledge of key events driving this transformation is limited to the paucity of comprehensive genomic data. We performed a retrospective database search in a CLIA- and CAP-certified laboratory for testicular GCT-derived ENTs that had previously undergone NGS-based comprehensive genomic profiling during the course of clinical care. Clinicopathological and genomic data were centrally re-reviewed. Here we report the molecular features of 10 ENTs of testicular GCT origin. All tumors harbored gain of chromosome 12p, often with KRAS, CCND2 and KMD5A co-amplification, supporting a germ cell origin. The tumors were microsatellite stable and exhibited low tumor mutational burden. Three tumors (30%) exhibited MYCN or MYC amplification with co-occurring inactivation of the p53 pathway via either TP53 mutations or MDM2 amplification in two tumors. Three additional tumors (30%) had activation of the PI3K pathway via PIK3CA and PIK3CG mutations or PIK3C2B amplification; one tumor with co-occurring CDK4 amplification. Gene rearrangements were detected in three tumors (30%), with novel BRD4-MAU2 and BCOR-CLIP2 fusions as well as an internal truncating ATRX rearrangement, respectively. In summary, ENTs arising from GCTs are molecularly heterogeneous; however, a large fraction of testicular ENTs could be stratified by two distinct sets of genetic alterations, including MYCN/MYC amplification with concurrent suppression of the p53 pathway, and activation of the PI3K pathway with co-occurring CDK4 amplification. Moreover, the novel gene fusions identified in a subset of testicular GCT-derived ENTs overlap with molecularly defined tumors of embryonic-type neuroectodermal features in the central nervous system, indicating the potential common driving events for tumorigenesis from different anatomic sites.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100702"},"PeriodicalIF":7.1,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142896074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Independent Validation of a HER2-low Focused IHC Scoring System for Enhanced Pathologist Precision and Consistency.","authors":"Gelareh Farshid, Jane Armes, Benjamin Dessauvagie, Amardeep Gilhotra, Beena Kumar, Hema Mahajan, Ewan Millar, Nirmala Pathmanathan, Cameron Snell","doi":"10.1016/j.modpat.2024.100693","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100693","url":null,"abstract":"<p><p>For two decades the ASCO CAP HER2 testing criteria have included 0 and 1+ scores, but this distinction was inconsequential. Now, based on the DESTINY Breast-04 Trial (DB-04) results, for patients with metastatic breast cancer it underpins eligibility for T-DXd treatment. Discerning 0 from 1+ IHC staining is challenging, as HER2 low is not a biologically distinct cancer subset, there are no reference standards or controls and second-tier tests do not apply. Prior reports cast doubt on the reliability of pathologists' IHC scoring, with resulting treatment misalignments. With IRB approval, our group of 9 breast pathologists from 8 Australian laboratories had previously established HER2-low focused scoring conventions, based on the ASCO CAP 2018 HER2 guidelines, and specifying common staining pitfalls. We reported the results of a first set of 60 breast cancers evaluated with these methods ¹. After a five-month washout, for the present validation study, we have compiled a second set of 64 HER2 negative invasive breast cancer core biopsies, all assessed with the Ventana 4B5 HER2 assay. We have each scored digitized images of HER2 IHC slides of the cases. Using the majority opinion as the target score, we have calculated our performance metrics. We have compared the results of our performance in set 1 and set 2 to assess the effectiveness of our approach and learning retention. The cases in this validation set included 40 (62.5%) HER2-low, 10 (17.2%) ultralow (UL) and 13 (18.8%) null cancers. Concordance was not achieved in one case. For distinguishing HER2 low from other cancers (UL and null combined) the mean values of our performance metrics were: accuracy 89.58%, sensitivity 90.83%, specificity 87.50%, positive predictive value: 95.63%, negative predictive value 83.59% and Cohen's kappa score 0.81. Comparing these results with our initial study, we have maintained our high level of performance across these parameters. Our mean kappa score is now in the excellent range for concordance. Maintaining high performance across a range of measures in two separate datasets validates the effectiveness of our HER2 low-focused scoring conventions. Having validated our approach, we will use these reference case sets with expert level consensus scores for peer training and updating our national HER2 IHC external quality assurance program. In our ongoing studies, we are also assessing the performance of software algorithms to determine their suitability for pre-screening of HER2 IHC slides.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100693"},"PeriodicalIF":7.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142895824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Pathology-Enabled Residual Tumor Estimation is a Prognostic Factor for Overall Survival in Anal Squamous Cell Carcinoma.","authors":"Paula Toro, Ahmed Bakhshwin, Bassel Zein-Sabatto, Neha Khaitan, Lauren Duckworth, Ana Bennett, Sarah S Elsoukkary, Xuefeng Zhang, Sneha Govande, Emily C Zabor, David Liska, Ehsan Balagamwala, Daniela S Allende","doi":"10.1016/j.modpat.2024.100692","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100692","url":null,"abstract":"<p><p>Anal squamous cell carcinoma (SCC) incidence has increased, and treatment has shifted from surgery to chemoradiotherapy (CRT), with salvage abdominoperineal resection (APR) being reserved for persistent/recurrent cases. This study evaluates the utility of different Tumor Regression Scoring Systems (TRSS) in predicting survival in anal SCC patients, using pathologists' observations and digital pathology. Cases managed surgically from 2005 to 2019 were collected. Residual tumor was assessed by multiple methods (gross tumor size, largest focus of tumor on H&E slide, average of residual tumor in all submitted H&E slides, JES, Chirieac, Schneider, Hermann, CAP scoring system). Three expert pathologists individually estimated (\"eyeballed\") the residual tumor % based on residual tumor/tumor bed (single representative H&E slide). The QuPath software was used to measure tumor volume on the same slide. American Joint Committee on Cancer (AJCC) 8th staging, and outcome data were retrieved from electronic medical records. The study involved 48 participants, predominantly female (56%), with a median age of 57. Most were Caucasian. HPV-positive was present in 77% of those assessed (17/22). Initial treatment included chemoradiation (CRT), followed by APR (79%) or pelvic exenteration (21%). Complications (13%), persistent disease (33%), and recurrence (54%) led to surgical interventions. 51% had moderately differentiated SCC, whereas 42% were poorly differentiated. Lymphovascular invasion (44%), perineural invasion (38%), and lymph node metastasis (13%) were present. Distant metastasis was rare (2%). Median overall survival was 3.2 years. Positive margins (HR 4.12, 95% CI 1.83, 9.28) and larger tumor size (HR 1.02 95% CI 1.01, 1.03) were associated with an increased hazard of death. Most residual tumor measurement methods were not significantly associated with overall survival. Interobserver agreement (based on \"eyeballing\") was moderate (kappa 0.4). Computational pathology-based residual tumor percentage was the only method significantly associated with outcome, with each 10% increase in the residual tumor percentage corresponding to a 1.23-fold higher hazard death (95% CI 1.03, 1.46; p=0.024). This study highlights computational pathology's important role in predicting outcomes in anal SCC treated with CRT and surgery. Specifically, the computational assessment of the residual tumor percentage proves to be a strong predictor of overall survival, outperforming other established TRSS methods.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100692"},"PeriodicalIF":7.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of Pathological Criteria and Immunohistochemical Evaluation for Invasive Lobular Carcinoma Diagnosis.","authors":"Seyed Reza Taha, Fouad Boulos","doi":"10.1016/j.modpat.2024.100665","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100665","url":null,"abstract":"","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":"38 2","pages":"100665"},"PeriodicalIF":7.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient and generalizable prediction of molecular alterations in multiple cancer cohorts using H&E whole slide images.","authors":"Kshitij Ingale, Sun Hae Hong, Qiyuan Hu, Renyu Zhang, Bolesław L Osinski, Mina Khoshdeli, Josh Och, Kunal Nagpal, Martin C Stumpe, Rohan P Joshi","doi":"10.1016/j.modpat.2024.100691","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100691","url":null,"abstract":"<p><p>Molecular testing of tumor samples for targetable biomarkers is restricted by a lack of standardization, turnaround-time, cost, and tissue availability across cancer types. Additionally, targetable alterations of low prevalence may not be tested in routine workflows. Algorithms that predict DNA alterations from routinely generated hematoxylin and eosin (H&E)-stained images could prioritize samples for confirmatory molecular testing. Costs and the necessity of a large number of samples containing mutations limit approaches that train individual algorithms for each alteration. In this work, models were trained for simultaneous prediction of multiple DNA alterations from H&E images using a multi-task approach. Compared to biomarker-specific models, this approach performed better on average, with pronounced gains for rare mutations. The models reasonably generalized to independent temporal-holdout, externally-stained, and multi-site TCGA test sets. Additionally, whole slide image embeddings derived using multi-task models demonstrated strong performance in downstream tasks that were not a part of training. Overall, this is a promising approach to develop clinically useful algorithms that provide multiple actionable predictions from a single slide.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100691"},"PeriodicalIF":7.1,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered TP53, CDKN2A, ATM, EPHA7, POT1, CHEK1, GRIN2A, and EGFR Predict Shorter Survival in Penile Squamous Cell Carcinoma.","authors":"Jan Hojný, Jan Hrudka, Zuzana Prouzová, Michaela Kendall Bártů, Eva Krkavcová, Jiří Dvořák, Romana Michálková, David Čapka, Nicolette Zavillová, Radoslav Matěj, Petr Waldauf","doi":"10.1016/j.modpat.2024.100689","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100689","url":null,"abstract":"<p><p>Penile squamous cell carcinoma (pSCC) represents an uncommon malignancy characterized by stagnant mortality, psychosexual distress, and a highly variable prognosis. Currently, the WHO distinguishes between human papillomavirus (HPV) related and HPV independent pSCC. Recently, there has been an evolving line of research documenting the enrichment of HPV-independent pSCC with a high tumor mutational burden (TMB) and programmed death ligand-1 (PD-L1) expression, as well as clusters of genes associated with HPV status. In this study, we conducted comprehensive next-generation sequencing (NGS) DNA profiling of 146 pSCC samples using a panel consisting of 355 genes associated with tumors. This profiling was correlated with immunohistochemical markers and prognostic clinical data. A survival analysis of recurrent genomic events (found in ≥10 cases) was performed. TP53, CDKN2A, ATM, EPHA7, POT1, CHEK1, GRIN2A, and EGFR alterations were associated with significantly shortened overall survival (OS) in univariate and multivariate analysis. HPV positivity, diagnosed through both p16 immunohistochemistry and HPV DNA analysis, displayed no impact on survival but was associated with high grade, lymphatic invasion, PD-L1 negativity/weak expression, and low TMB. FAT1, TP53, CDKN2A, CASP8, and HRAS were more often mutated in HPV-independent pSCC. In contrast, HPV associated pSCCs were enriched by EPHA7, ATM, GRIN2A and CHEK1 mutations. PIK3CA, FAT1, FBXW7, and KMT2D mutations were associated with high TMB. NOTCH1, TP53, CDKN2A, POT1, KMT2D, ATM, CHEK1, EPHA3, and EGFR alterations were related with adverse clinical-pathological signs such as advanced stage, high tumor budding, and lymphovascular invasion. We detected 160 alterations with potential treatment implications, with 21.2% of samples showing alterations in the homologous recombination pathway. To the best of our knowledge, this study describes the largest cohort of pSCC with complex molecular-pathological, clinical, and prognostic analysis correlating with prognosis.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100689"},"PeriodicalIF":7.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142854726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ethical and Bias Considerations in Artificial Intelligence (AI)/Machine Learning.","authors":"Matthew Hanna, Liron Pantanowitz, Brian Jackson, Octavia Palmer, Shyam Visweswaran, Joshua Pantanowitz, Mustafa Deebajah, Hooman Rashidi","doi":"10.1016/j.modpat.2024.100686","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100686","url":null,"abstract":"<p><p>As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications and potential biases within such integrated AI models will require careful scrutiny. Ethics and bias are important considerations in our practice settings, especially as increased number of machine learning (ML) systems are being integrated within our various medical domains. Such machine learning based systems, have demonstrated remarkable capabilities in specified tasks such as but not limited to image recognition, natural language processing, and predictive analytics. However, the potential bias that may exist within such AI-ML models can also inadvertently lead to unfair and potentially detrimental outcomes. The source of bias within such machine learning models can be due to numerous factors but can be typically put in three main buckets (data bias, development bias and interaction bias). These could be due to the training data, algorithmic bias, feature engineering and selection issues, clinical and institutional bias (i.e. practice variability), reporting bias, and temporal bias (i.e. changes in technology, clinical practice or disease patterns). Therefore despite the potential of these AI-ML applications, their deployment in our day to day practice also raises noteworthy ethical concerns. To address ethics and bias in medicine, a comprehensive evaluation process is required which will encompass all aspects such systems, from model development through clinical deployment. Addressing these biases is crucial to ensure that AI-ML systems remain fair, transparent, and beneficial to all. This review will discuss the relevant ethical and bias considerations in AI-ML specifically within the pathology and medical domain.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100686"},"PeriodicalIF":7.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142854749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Etiology and outcomes of kidney-limited and systemic thrombotic microangiopathy.","authors":"Daan P C van Doorn, Rachid Tobal, Myrurgia A Abdul-Hamid, Pieter van Paassen, Sjoerd A M E G Timmermans","doi":"10.1016/j.modpat.2024.100690","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100690","url":null,"abstract":"<p><p>The syndromes of thrombotic microangiopathy (TMA) are associated with acute kidney injury and end-stage kidney disease (ESKD). TMAs typically present with thrombocytopenia and microangiopathic hemolytic anemia (i.e., systemic TMA). Kidney-limited TMA can occur, although often overlooked and undertreated. Here, we studied the etiology and outcome of kidney-limited TMA. Patients with TMA on kidney biopsy, either systemic or kidney-limited TMA, were recruited and classified as definite complement-mediated (C-)TMA (i.e., ≥1 pathogenic complement gene variant), probable C-TMA (i.e., massive ex vivo C5b9 formation without a pathogenic complement gene variant), and non (n)C-TMA (i.e., normal ex vivo C5b9 formation). Morphologic features of TMA on kidney biopsy and their clinical correlates were studied. Patients were classified as definite C-TMA (N=14, 18%), probable C-TMA (N=21, 27%), or nC-TMA (N=42, 55%), including 51 (66%) out of 77 patients with kidney-limited TMA. Patients with definite and probable C-TMA often presented with hemolysis (79% and 62% versus 34%; P=0.007), glomerular thrombosis (79% and 76% versus 43%), higher creatinine (974 and 502 versus 280 μmol/L; P=0.001), and younger age (33 and 33 versus 40 years; P=0.029) as compared to nC-TMA. Morphologic features neither defined etiology nor differed between systemic and kidney-limited TMA. Eculizumab improved kidney outcomes in patients with kidney-limited C-TMA but not in those with nC-TMA akin to patients with systemic C-TMA. Kidney outcomes were not affected by chronicity grading on kidney biopsy. Kidney-limited TMA is common in the diverse TMAs, including C-TMA. A kidney biopsy is needed to detect the TMA at the earliest possible stage of disease. Morphology does not allow for the identification of etiology and patients with kidney-limited TMA should therefore be screened for complement dysregulation, having major impact on treatment and prognosis.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100690"},"PeriodicalIF":7.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142854737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative Artificial Intellegence (AI) in Pathology and Medicine: A Deeper Dive.","authors":"Hooman H Rashidi, Joshua Pantanowitz, Alireza Chamanzar, Brandon Fennell, Yanshan Wang, Rama R Gullapalli, Ahmad Tafti, Mustafa Deebajah, Samer Albahra, Eric Glassy, Mathew Hanna, Liron Pantanowitz","doi":"10.1016/j.modpat.2024.100687","DOIUrl":"https://doi.org/10.1016/j.modpat.2024.100687","url":null,"abstract":"<p><p>This review article builds upon the introductory piece in our seven-part series, delving deeper into the transformative potential of generative artificial intelligence (Gen AI) in pathology and medicine. The article explores the applications of Gen AI models in pathology and medicine, including the use of custom chatbots for diagnostic report generation, synthetic image synthesis for training new models, dataset augmentation, hypothetical scenario generation for educational purposes, and the use of multimodal along with multi-agent models. This article also provides an overview of the common categories within generative AI models, discussing open-source and closed-source models, as well as specific examples of popular models such as GPT-4, Llama, Mistral, DALL-E, Stable Diffusion and their associated frameworks (e.g. transformers, GANs, diffusion-based neural networks), along with their limitations and challenges, especially within the medical domain. We also review common libraries, and tools that are currently deemed necessary to build and integrate such models. Finally, we look to the future, discussing the potential impact of generative AI on healthcare, including benefits, challenges, and concerns related to privacy, bias, ethics, API costs, and security measures.</p>","PeriodicalId":18706,"journal":{"name":"Modern Pathology","volume":" ","pages":"100687"},"PeriodicalIF":7.1,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142847012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}