A study using AI methods to examine the effects of malnutrition on cancer patients' life expectancies
The study aims to collect information from cancer patients about the factors leading to malnutrition and predict the patient's recovery.
Rationale of the research:
1. Cancer patients who are malnourished have a greater likelihood of succumbing to cancer from their disease. Malnourished patients are more likely to die from cancer as well as other conditions like infections and cardiovascular disease.
2. A cancer patient's quality of life may be significantly impacted by malnutrition, which can also have an adverse effect on their mental health and energy levels. Malnourished patients may also engage in less social interaction and feel less well-being.
3.The efficacy of cancer treatments like chemotherapy and radiation therapy can potentially be hampered by malnutrition. Malnourished patients may have lower blood cell counts, compromised immune systems, and lowered tolerance to therapy, all of which might make it more difficult to get a good result.
4. Patients with cancer are at an increased risk of developing problems such as infections, sluggish wound healing, and loss of strength and muscle mass due to malnutrition. This can make it harder for patients to endure the treatment, which might result in extended hospital stays and suboptimal results.
Novelty of the research:
The novelty of this proposed study is to assist healthcare professionals from Mumbai in identifying cancer patients who would be malnourished. This would make it possible for the caregiver to better support cancer patients in their fight against the disease.
Objectives:
1. To study the factors responsible for malnutrition.
2. To collect the data of cancer patients and classify it for malnutrition.
3. To study the relationship between malnutrition and cancer. (Study of malnutrition on cancer patients w.r.t. gender, age etc..)
4. To study the impact of malnutrition on life expectancy of cancer patient using supervised learning techniques of AI
Dr. Anita Chaware, Associate Professor, P. G. Department of Computer Science, S.N.D.T. Women's University.