Artificial intelligence and machine learning show promise in cancer diagnosis and treatment

Artificial Intelligence (AI), Deep Learning (DL) and Machine Learning (ML) have transformed many industries and scientific fields

"The biomarker field has a plethora of imaging and molecular data and, at the same time, too much data that no one can fully understand," explained Dr.

Promising applications of AI, DL, and ML presented in this issue include identifying early-stage cancers, inferring the location of specific cancers, helping to assign appropriate treatment options to each patient, characterizing the tumor microenvironment, and predicting response to immunotherapy

A comprehensive overview of the literature on the use of artificial intelligence methods to identify biomarkers in ovarian and pancreatic cancer illuminates the underlying principles and provides a holistic look at the gaps and challenges facing the field

"When algorithms are trained on data that is not representative or incomplete, they become biased and produce biased responses," Dr.

Principal investigator Debiao Li, Ph.

"The challenge of artificial intelligence for pancreatic cancer research progress is that data is scarce due to the low incidence

Radiomics is an emerging field that utilizes various techniques to extract features from medical imaging

They observed: "This model could provide more accurate information about potential recurrence and metastasis and may aid in decision-making

Other papers in the special issue focus on developing new computational tools to facilitate the use of artificial intelligence in biomarker identification; identifying immune signatures of pancreatic tumors using whole-cell imaging and immunofluorescence to provide prognostic information; using microRNAs and applying machine learning to identify miRNA profiles associated with gastrointestinal stromal tumors; and use hierarchical clustering combined with multiple datasets to identify antitumor immune signatures in colon cancer patients

Dr.

Leading experts comment on special issue

Anirban Maitra, MD, Anderson Cancer Center

As the fields of cancer research and clinical care expand, with ever-increasing datasets and data integration across different platforms, it's no surprise that AI and ML are increasingly being used in oncology

Dr.

Advances in machine learning are affecting our daily lives in more and more ways

Chris Amos, Ph.

This special issue brings together a wealth of new approaches to applying new technologies in machine learning and artificial intelligence, as well as advances in high-throughput biomarker analysis to identify patterns that identify individuals at high risk for cancer

Dr.
Samir M.
Hanash, Anderson Cancer Center

Current interest in biomarkers spans the need for personalized cancer treatment and monitoring of disease progression and recurrence to cancer risk assessment and early detection
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From genomics to proteomics and metabolomics, biomarker discovery has a wide range of platforms that can generate massive amounts of data that benefit from artificial intelligence data analysis methods
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This special issue is timely as it discusses the application of artificial intelligence in cancer research and the contribution of artificial intelligence in improving cancer detection and diagnosis through biomarker discovery
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