After analyzing the last 25 years of data, then we try to develop a predictive model with our machine learning thing, our MX model, and we found astonishing results. In 2030, the lung cancer modality is not going to go down as well as it did in the last 25 years. So, because of what, because they have developed their HDI index very much, almost perfect to one. They have developed so many drugs, they have developed strict controls on PM and environmental levels, as well as anti-tobacco policies...
After analyzing the last 25 years of data, then we try to develop a predictive model with our machine learning thing, our MX model, and we found astonishing results. In 2030, the lung cancer modality is not going to go down as well as it did in the last 25 years. So, because of what, because they have developed their HDI index very much, almost perfect to one. They have developed so many drugs, they have developed strict controls on PM and environmental levels, as well as anti-tobacco policies. But still, there is something to do to reduce lung cancer mortality for the next 30 years. So now we have to focus on why lung cancer mortality is not going down in the next 25 years. What are the other factors impeding it? Now we are looking for other factors like gender issues. We are trying to find out if male lung cancer and female lung cancer are the same or not. So we have to focus on that thing and we have to also focus on what are the recurrence and relapses of the disease. So when we are treating lung cancer with so many drugs, the mutation pathway, the pathogenesis, everything is changing. So we have to focus on the other parts. You know, interestingly, there are some mutations for which we have drugs only for 30% of lung cancer, but the rest of the 70% we treat patients only with chemotherapy drugs. So we need to focus on that part. What are the delivery systems of the drugs? What are the new chemotherapy drugs we need? So that is the main challenge for the next 30 years. I think we should have some other concerns regarding gender biasness as well as developing the drug delivery system so that we can improve patient outcomes as well as reduce the mortality of patients.
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