From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …
Artificial intelligence for digital and computational pathology
Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …
including deep learning, have boosted the field of computational pathology. This field holds …
Towards a general-purpose foundation model for computational pathology
Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks,
requiring the objective characterization of histopathological entities from whole-slide images …
requiring the objective characterization of histopathological entities from whole-slide images …
A visual-language foundation model for computational pathology
The accelerated adoption of digital pathology and advances in deep learning have enabled
the development of robust models for various pathology tasks across a diverse array of …
the development of robust models for various pathology tasks across a diverse array of …
A guide to artificial intelligence for cancer researchers
Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to
a readily accessible tool for cancer researchers. AI-based tools can boost research …
a readily accessible tool for cancer researchers. AI-based tools can boost research …
[HTML][HTML] Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer …
Liver cancers are the fourth leading cause of cancer-related mortality worldwide. In the past
decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of …
decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of …
[HTML][HTML] Application of radiomics-based multiomics combinations in the tumor microenvironment and cancer prognosis
W Kang, X Qiu, Y Luo, J Luo, Y Liu, J Xi, X Li… - Journal of Translational …, 2023 - Springer
The advent of immunotherapy, a groundbreaking advancement in cancer treatment, has
given rise to the prominence of the tumor microenvironment (TME) as a critical area of …
given rise to the prominence of the tumor microenvironment (TME) as a critical area of …
Quantitative multiplexed imaging technologies for single-cell analysis to assess predictive markers for immunotherapy in thoracic immuno-oncology: promises and …
The past decade has witnessed a revolution in cancer treatment by the shift from
conventional drugs (chemotherapies) towards targeted molecular therapies and immune …
conventional drugs (chemotherapies) towards targeted molecular therapies and immune …
Revolutionizing digital pathology with the power of generative artificial intelligence and foundation models
Digital pathology has transformed the traditional pathology practice of analyzing tissue
under a microscope into a computer vision workflow. Whole slide imaging allows …
under a microscope into a computer vision workflow. Whole slide imaging allows …
Artificial intelligence in clinical oncology: from data to digital pathology and treatment
Recently, a wide spectrum of artificial intelligence (AI)–based applications in the broader
categories of digital pathology, biomarker development, and treatment have been explored …
categories of digital pathology, biomarker development, and treatment have been explored …