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On Thu, 9 Jan, 8:02 AM UTC
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Using AI to predict the outcome of aggressive skin cancers
Artificial intelligence can determine the course and severity of aggressive skin cancers, such as Merkel cell carcinoma (MCC), to enhance clinical decision making by generating personalised predictions of treatment specific outcomes for patients and their doctors. An international team, led by researchers at Newcastle University, UK, combined machine learning with clinical expertise to develop a web-based system called "DeepMerkel" which offers the power to predict MCC treatment specific outcomes based on personal and tumour specific features. They propose that this system could be applied to other aggressive skin cancers for precision prognostication, the enhancement of informed clinical decision making and improved patient choice. MCC MCC is a rare but highly aggressive skin cancer. It can be difficult to treat -- typically affecting older adults with weakened immune systems who present with advanced disease associated with poor survival. Dr Tom Andrew, a Plastic Surgeon and CRUK funded PhD student at Newcastle University and first author said; "DeepMerkel is allowing us to predict the course and severity of a Merkel cell carcinoma enabling us to personalise treatment so that patients are getting the optimal management. "Using AI allowed us to understand subtle new patterns and trends in the data which meant on an individual level, we are able to provide more accurate predictions for each patient. "This is important as in the 20 years up to 2020, the number of people diagnosed with this cancer has doubled and while it is still rare it is an aggressive skin cancer which is increasingly affecting older people." The research was conducted with Penny Lovat, Professor of Dermato-oncology, Newcastle University, and Dr Aidan Rose, Senior Clinical Lecturer, Newcastle University and Consultant Plastic Surgeon at Newcastle Hospitals NHS Foundation Trust. Dr Rose said; "Being able to accurately predict patient outcomes is critical when guiding clinical decision making. This is particularly important when treating aggressive forms of skin cancer in a complex patient group which typically results in difficult, and sometime life-changing, choices being made regarding treatment options. The developments we have made using AI allow us to provide personalised survival predictions and inform a patient's medical team of the optimal treatment." In two complementary publications in Nature Digital Medicine and the Journal of the American Academy of Dermatology, the team describe how using advanced statistical and machine learning methods they developed the web-based prognostic tool for MCC. Method In Nature Digital Medicine, the team describe how they employed explainability analysis and the data of to reveal new insights into mortality risk factors for the highly aggressive cancer, MCC. They then combined deep learning feature selection with a modified XGBoost framework, to develop a web-based prognostic tool for MCC which they termed DeepMerkel. Analysing the data from nearly 11,000 patients in 2 countries, the researchers describein the Journal of the American Academy of Dermatology how DeepMerkel was able to accurately identify high-risk patients at an earlier stage of the cancer. This allows medics to make more informed decisions about when to use radical treatment options and intensive disease monitoring. Patients first The team hope that DeepMerkel will provide better information for patients to make decisions with their medical teams about the best treatment for them as an individual. Dr Andrew added: "With further investment, the exciting next step for our team is to further develop DeepMerkel so that the system can present options to help advise clinicians on the best treatment pathway open to them." The next step is to integrate the DeepMerkel website into routine clinical practice and broaden the scope of its use into other tumour types.
[2]
Using AI to predict the outcome of aggressive skin cancers
Artificial intelligence can determine the course and severity of aggressive skin cancers, such as Merkel cell carcinoma (MCC), to enhance clinical decision making by generating personalized predictions of treatment-specific outcomes for patients and their doctors. An international team, led by researchers at Newcastle University, UK, combined machine learning with clinical expertise to develop a web-based system called "DeepMerkel" which offers the power to predict MCC treatment-specific outcomes based on personal and tumor specific features. They propose that this system could be applied to other aggressive skin cancers for precision prognostication, the enhancement of informed clinical decision making and improved patient choice. MCC is a rare but highly aggressive skin cancer. It can be difficult to treat -- typically affecting older adults with weakened immune systems who present with advanced disease associated with poor survival. Dr. Tom Andrew, a Plastic Surgeon, Ph.D. student at Newcastle University, and first author said, "DeepMerkel is allowing us to predict the course and severity of a Merkel cell carcinoma enabling us to personalize treatment so that patients are getting the optimal management. "Using AI allowed us to understand subtle new patterns and trends in the data which meant on an individual level, we are able to provide more accurate predictions for each patient. "This is important as in the 20 years up to 2020, the number of people diagnosed with this cancer has doubled and while it is still rare it is an aggressive skin cancer which is increasingly affecting older people." The research was conducted with Penny Lovat, Professor of Dermato-oncology, Newcastle University, and Dr. Aidan Rose, Senior Clinical Lecturer, Newcastle University and Consultant Plastic Surgeon at Newcastle Hospitals NHS Foundation Trust. Dr. Rose said, "Being able to accurately predict patient outcomes is critical when guiding clinical decision making. This is particularly important when treating aggressive forms of skin cancer in a complex patient group which typically results in difficult, and sometimes life-changing, choices being made regarding treatment options. The developments we have made using AI allow us to provide personalized survival predictions and inform a patient's medical team of the optimal treatment." In two complementary publications in npj Digital Medicine and the Journal of the American Academy of Dermatology, the team describe how they developed the web-based prognostic tool for MCC using advanced statistical and machine learning methods. Method In npj Digital Medicine, the team describe how they employed explainability analysis and the data to reveal new insights into mortality risk factors for the highly aggressive cancer, MCC. They then combined deep learning feature selection with a modified XGBoost framework, to develop a web-based prognostic tool for MCC which they termed DeepMerkel. Analyzing the data from nearly 11,000 patients in 2 countries, the researchers describe in the Journal of the American Academy of Dermatology how DeepMerkel was able to accurately identify high-risk patients at an earlier stage of the cancer. This allows medics to make more informed decisions about when to use radical treatment options and intensive disease monitoring. Patients first The team hope that DeepMerkel will provide better information for patients to make decisions with their medical teams about the best treatment for them as an individual. Dr. Andrew added, "With further investment, the exciting next step for our team is to further develop DeepMerkel so that the system can present options to help advise clinicians on the best treatment pathway open to them." The next step is to integrate the DeepMerkel website into routine clinical practice and broaden the scope of its use into other tumor types.
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Researchers at Newcastle University have developed an AI system called DeepMerkel that can predict the course and severity of aggressive skin cancers, particularly Merkel cell carcinoma, enhancing clinical decision-making and personalized treatment.
Researchers at Newcastle University have developed a groundbreaking artificial intelligence system called "DeepMerkel" that can predict the course and severity of aggressive skin cancers, particularly Merkel cell carcinoma (MCC). This innovative tool combines machine learning with clinical expertise to enhance clinical decision-making and provide personalized treatment options for patients 12.
MCC is a rare but highly aggressive form of skin cancer that primarily affects older adults with weakened immune systems. The incidence of MCC has doubled in the 20 years leading up to 2020, making it an increasingly significant concern in the medical community 1.
DeepMerkel is a web-based system that utilizes advanced statistical and machine learning methods to generate personalized predictions of treatment-specific outcomes. The researchers employed explainability analysis and deep learning feature selection combined with a modified XGBoost framework to develop this tool 12.
The team analyzed data from nearly 11,000 patients across two countries to validate DeepMerkel's effectiveness. The system demonstrated the ability to accurately identify high-risk patients at earlier stages of cancer, enabling medical professionals to make more informed decisions about treatment options and disease monitoring 12.
Dr. Tom Andrew, a Plastic Surgeon and PhD student at Newcastle University, emphasized the importance of DeepMerkel in personalizing treatment:
"DeepMerkel is allowing us to predict the course and severity of a Merkel cell carcinoma enabling us to personalize treatment so that patients are getting the optimal management." 1
The AI system's ability to recognize subtle patterns and trends in the data allows for more accurate predictions on an individual level, potentially improving patient outcomes 2.
The researchers propose that the DeepMerkel system could be applied to other aggressive skin cancers, enhancing precision in prognosis and informed clinical decision-making. Dr. Aidan Rose, a Senior Clinical Lecturer at Newcastle University and Consultant Plastic Surgeon, highlighted the critical nature of accurate outcome predictions in guiding treatment choices for complex patient groups 12.
The team's next steps include further development of DeepMerkel to provide treatment pathway recommendations to clinicians and integration of the system into routine clinical practice. They also aim to expand its application to other tumor types, potentially revolutionizing cancer care across multiple domains 12.
The development of DeepMerkel represents a significant advancement in the use of AI for cancer prognosis and treatment planning. By providing personalized predictions and enhancing clinical decision-making, this tool has the potential to improve outcomes for patients with aggressive skin cancers and pave the way for similar applications in other areas of oncology.
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A new AI model developed by researchers at Ahmadu Bello University has achieved high accuracy in detecting skin cancer, potentially revolutionizing early diagnosis and treatment.
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Researchers develop an AI model that integrates diverse medical data to improve personalized cancer care, potentially revolutionizing treatment approaches and patient outcomes.
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2 Sources
Stanford Medicine researchers develop MUSK, an AI model that combines visual and text data to accurately predict cancer prognoses and treatment responses, outperforming standard methods.
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Recent studies demonstrate the potential of AI in improving prostate cancer risk stratification and predicting treatment outcomes, potentially revolutionizing patient care and treatment planning.
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A new study reveals that a ChatGPT like AI language model can effectively assist in cancer treatment decisions, potentially improving patient outcomes and survival rates. This development marks a significant step in the integration of AI in healthcare.
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