Wellbeing and aftercare

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Despite the increasing adaptation of treatments to individual cancer types and patients, and the development of technologies that reduce damage to healthy tissues, cancer therapy can be difficult to undergo, causing discomfort and distress. The following datasets relate to technologies that provide relief to patients and reduce the risk of cancer recurrence. They improve the wellbeing of patients during and after therapy.

Nutritional support and supplementation

Nutritional support is essential for patients undergoing cancer therapy. Cancer therapy can cause a variety of side effects that can make it difficult to eat and drink normally. As a result, many cancer patients lose weight and become malnourished. Nutritional support can help cancer patients maintain their weight and strength during cancer therapy. It improves their quality of life and reduces the risk of complications.

The following datasets concern diet and supplements supporting patients during and after therapy.

Diet during and post-therapy

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Vitamins during and post-therapy

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Minerals during and post-therapy

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Mitigating side effects

Cancer therapy can cause various side effects that depend on the type of cancer and the treatment used. Although most side effects are temporary and disappear once treatment is over, it is essential to manage them to improve the patient's quality of life. The following datasets relate to drugs that help to overcome specific side effects.

Anaemia is when the blood lacks healthy red blood cells, causing fatigue, shortness of breath and other symptoms.


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Mucositis is a common side effect of cancer treatment. It is an inflammation of the mucous membranes of the digestive tract, mouth, nose and throat.


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Nausea is a common side effect of cancer treatment. It is the feeling that you are about to vomit.


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Neutropenia is a condition in which the body does not have enough neutrophils (a type of immune cell) to help the body fight infection.


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Thrombocytopenia is a condition that occurs when the blood platelet count is too low (platelets contribute to blood coagulation).


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Predicting relapse

Computer-aided modelling uses large datasets of cancer patient records to develop models that can predict the risk of cancer recurrence and relapse risk. These models are more accurate than traditional methods of predicting cancer recurrence and relapse. They can help clinicians make follow-up care decisions and monitor the patient's post-therapy.

Artificial intelligence and prediction of cancer recurrence

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