Clinical use of machine learning‐based pathomics signature for diagnosis and survival prediction of bladder cancer

Siteng Chen, Liren Jiang, Xinyi Zheng, Jialiang Shao, Tao Wang, Encheng Zhang, Feng Gao, Xiang Wang et al.

Cancer Science 2021 article cited by 100

Source Open-access PDF More in Medicine & Health

importance 6/10 partially solved AI in cancer detection oncology diagnostics stage: research

Problem

Diagnosing bladder cancer accurately from tissue slides, where visual inspection by pathologists is insufficient.

Why it matters

Misdiagnosis of bladder cancer delays treatment and affects patient survival.

What the AI did

A machine learning algorithm learned from H&E-stained image pathomics data to automatically diagnose bladder cancer and predict survival.

Results

AUC 96.3% (training), 89.2% (test), 94.1% (external validation); 93.4% vs glandular cystitis; HR 2.09 (95% CI 1.56-2.81, P<.0001)

Impact

Externally validated model could aid pathologists in bladder cancer diagnosis and prognosis.

Record

Venue	Cancer Science
Published	2021
Work type	article
Authors	Siteng Chen, Liren Jiang, Xinyi Zheng, Jialiang Shao, Tao Wang, Encheng Zhang, Feng Gao, Xiang Wang et al.
Citations	100 (OpenAlex, at import time)
References	24
Model or method	not stated in source
Organization	not stated in source
Primary source	https://doi.org/10.1111/cas.14927
Open access	gold
Keywords	machine learning, pathomics, bladder cancer, histopathology, survival prediction

Importance rating

6 / 10

significant — thousands to millions affected

Abstract states histopathology is insufficient for accurate bladder cancer diagnosis; model aids diagnosis and prognosis, but no patient numbers or disease prevalence are stated.

Basis: inferred. Judged from the source text, which gives no explicit scale. Stated scale: not stated in source. Method and limits.

More in Medicine & Health

#	Paper	Year	Citations	Importance
1	Multimodal deep learning of fundus abnormalities and traditional risk factors for cardiovascular risk prediction Yeong Chan Lee, Jiho Cha, Injeong Shim, Woong‐Yang Park, Se Woong Kang...	2023	107	10
2	Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization Tawsifur Rahman, Amith Abdullah Khandakar, Muhammad Abdul Kadir, Khand...	2020	651	10
3	A comparative analysis of machine learning classifiers for stroke prediction: A predictive analytics approach Nitish Biswas, Khandaker Mohammad Mohi Uddin, Sarreha Tasmin Rikta, Sa...	2022	116	10
4	Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning Hamada R. H. Al-Absi, Mohammad Tariqul Islam, Mahmoud Ahmed Refaee, Mu...	2022	89	10
5	Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential Kruthi Suvarna, Deeptarup Biswas, Medha Gayathri J. Pai, Arup Acharjee...	2021	76	10