[HTML][HTML] Toward explainable artificial intelligence for precision pathology

F Klauschen, J Dippel, P Keyl… - Annual Review of …, 2024 - annualreviews.org
The rapid development of precision medicine in recent years has started to challenge
diagnostic pathology with respect to its ability to analyze histological images and …

[HTML][HTML] MGMT and whole-genome DNA methylation impacts on diagnosis, prognosis and therapy of glioblastoma multiforme

R Della Monica, M Cuomo, M Buonaiuto… - International Journal of …, 2022 - mdpi.com
Epigenetic changes in DNA methylation contribute to the development of many diseases,
including cancer. In glioblastoma multiforme, the most prevalent primary brain cancer and …

[HTML][HTML] Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a narrative review

C Ladbury, R Zarinshenas, H Semwal… - Translational Cancer …, 2022 - ncbi.nlm.nih.gov
Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a
narrative review - PMC Back to Top Skip to main content NIH NLM Logo Access keys NCBI …

A comprehensive study of explainable artificial intelligence in healthcare

A Mohanty, S Mishra - Augmented intelligence in healthcare: A pragmatic …, 2022 - Springer
The recent development of Artificial intelligence and Machine learning, in general, has
exhibited impressive results in a variety of fields, especially through the introduction of deep …

Identification of crucial genes for predicting the risk of atherosclerosis with system lupus erythematosus based on comprehensive bioinformatics analysis and machine …

C Liu, Y Zhou, Y Zhou, X Tang, L Tang… - Computers in Biology and …, 2023 - Elsevier
Background Systemic lupus erythematosus (SLE) has become a major public health
problem over the years, and atherosclerosis (AS) is one of the main complications of SLE …

[HTML][HTML] Deep-learning model for tumor-type prediction using targeted clinical genomic sequencing data

M Darmofal, S Suman, G Atwal, M Toomey, JF Chen… - Cancer discovery, 2024 - AACR
Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis
remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor …

HiTAIC: hi erarchical tumor artificial intelligence classifier traces tissue of origin and tumor type in primary and metastasized tumors using DNA methylation

Z Zhang, Y Lu, S Vosoughi, JJ Levy… - NAR …, 2023 - academic.oup.com
Human cancers are heterogenous by their cell composition and origination site. Cancer
metastasis generates the conundrum of the unknown origin of migrated tumor cells. Tracing …

Deep learning and machine learning approaches to classify stomach distant metastatic tumors using DNA methylation profiles

J Shi, Y Chen, Y Wang - Computers in Biology and Medicine, 2024 - Elsevier
Distant metastasis of cancer is a significant contributor to cancer-related complications, and
early identification of unidentified stomach adenocarcinoma is crucial for a positive …

[HTML][HTML] From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies

A Mukherjee, S Abraham, A Singh, S Balaji… - Molecular …, 2024 - Springer
In the dynamic landscape of targeted therapeutics, drug discovery has pivoted towards
understanding underlying disease mechanisms, placing a strong emphasis on molecular …

[HTML][HTML] A molecular approach integrating genomic and DNA methylation profiling for tissue of origin identification in lung-specific cancer of unknown primary

K Chen, F Zhang, X Yu, Z Huang, L Gong, Y Xu… - Journal of translational …, 2022 - Springer
Background Determining the tissue of origin (TOO) is essential for managing cancer of
unknown primary (CUP). In this study, we evaluated the concordance between genome …