Skin disease detection

Project Title

Skin disease detection

Project Area of Specialization Artificial IntelligenceProject Summary

In the skin disease detection we are collecting the dataset of maleria cell.Because maleria continues to claim the lives of more than 435 000 people each year.like in other parts of the world maleria is a leading cause of morbility and mortality in pakistan .It is one of the 6 priority communicable disease posting threat to the health of millions.by using matlab tool we point out the effected area and detect the affected area by using artifical intelligence mechanism. in this way we are easily find out that in which disease patient are suffering . IS there is any affected area or not . we can not move to the third party doctor and we can not testing the blood . because by applying this method we can eaily find out the disease .

Project Objectives

Parasites lives on host organism with some or complete metabolic dependence on it, while the haemoparasites inhabit and nourished from blood cells of the host. The current investigation evaluated to raise awareness of blood parasite (Plasmodium spp.) infection in pakistan population and to know as to which Plasmodium species was most prevalent. One year data was collected from different hospitals and laboratories of the Pakistan, blood slides were prepared under the microscope. Four hundred and eighty one infected slides with Plasmodium were observed amongst them 396 (82.32 percent) had P. vivax and 85 (17.67 percent) had P. falciparum infection. The rate of infection did not vary with gender but had a signification association with age. Highest incidence was recorded in age group 16-40 years for both P. vivax and P. falciparum followed by age group 1-15 years in P. vivax and age group 41-60 years for P. falciparum. It is mostly associated with poverty and consequently has a negative effect on economic development To solve these mechanism we are using the software tool and artificial intelligence

Project Implementation Method

Maleria research follows two distinct, and to some extent competing, methods, the symbolic (or “top-down”) approach, and the connectionist (or “bottom-up”) approach. In a way, Machine Learning works in a similar way to human learning. For example, if a child is shown images with specific objects on them, they can learn to identify and differentiate between them. Machine Learning works in the same way: Through data input and certain commands, the computer is enabled to "learn" to identify certain objects (persons, objects, etc.) and to distinguish between them. For this purpose, the software is supplied with data and trained. For instance, the programmer can tell the system that a particular object is a human being  and another object is not a human being . The software receives continuous feedback from the programmer. These feedback signals are used by the algorithm to adapt and optimize the model. With each new data set fed into the system, the model is further optimized so that it can clearly distinguish between "humans" and "non-humans" in the end.

Benefits of the Project

it is helpful to detect the infected area of maleria disease without any medical test we can easily found that which disease patient are suffering . is the infected area is Plasmodium or not . by appling this method we can eaily found the infected area.

Technical Details of Final Deliverable

• a clear description of all processes, interventions and comparisons. Generic names should generally be used. When proprietary brands are used in research, include the brand names in parentheses
• the type of statistical analysis used, including a power calculation if appropriate

Final Deliverable of the Project Software SystemCore Industry MedicalOther Industries Health Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	5000
software based things	Miscellaneous	1	5000	5000