--That Have Two Part--
01. Image classification Model - It Makes Using Python with Tensorflow
02. Mobile Application - Flutter
Sri Lanka holds a unique position in South Asia as one of the least developed nations that have provided a better opportunity for universal health, free education, and social mobility. The history of Sri Lankan medicine over the centuries has been shaped by a synthesis of several internal and external factors. Some of them were unique to the country. Ayurvedic medical system is endemic to Sri Lanka and has been practiced throughout the island for centuries. The Sri Lankan Ayurvedic tradition is the collection of Sinhala traditional medicine, Ayurvedic and Siddha methods in India, Unani medicine in Greece through the Arabs, and most importantly the Desheeya Chikitsa, which is the indigenous medicine of Sri Lanka. The earliest medicine that prevailed in Sri Lanka was desiya chikitsa which was passed down from generation to generation. Indigenous Hela Vedakama used in the past is moving away from society today. A large number of patients are turning to western medicine, suppressing Sinhala Ayurveda medical system. Today a variety of patients are reported from Sri Lanka. For example, heart diseases, cancers, diabetes, chronic kidney disease, Skin diseases, strokes, and osteoporosis among many other diseases. Skin diseases are one of the most commonly reported diseases in Sri Lanka. Skin disorders vary greatly in symptoms and severity. It can be temporary or permanent and can be painless or painful. Some have situational causes, while others may be genetic. Some skin conditions are minor, and others can be life-threatening. While most skin disorders are minor, others can indicate a more serious issue. There are many different types of skin disorders. Skin disorders can be divided into permanent skin disorders and temporary skin disorders.
Permanent skin disorders
Some chronic skin conditions are present from birth, while others appear suddenly later
in life. The cause of these disorders isn’t always known. Many permanent skin disorders
have effective treatments that enable extended periods of remission. However, they’re
incurable, and symptoms can reappear at any time. Examples of chronic skin conditions
include:
▪ Rosacea, which is characterized by small, red, pus-filled bumps on the face
▪ Psoriasis, which causes scaly, itchy, and dry patches
▪ Vitiligo, which results in large, irregular patches of skin
Skin diseases have a serious impact on people’s life and health. Skin diseases are more
common than other diseases. Skin diseases may be caused by a fungal infection,
bacteria, allergy, or viruses, etc. Skin disease may change the texture or color of the
skin. In general, skin diseases are chronic, infectious, and sometimes may develop into
skin cancer. Therefore, skin diseases must be diagnosed early to reduce their
development and spread. The diagnosis and treatment of a skin disease takes a long
time and causes financial costs to the patient. In general, most common people do not
know the type and stage of skin disease. Some of the skin diseases show symptoms
several months later, causing the disease to develop and grow further. This is due to the
lack of medical knowledge in the public. Sometimes, a dermatologist (skin specialist
doctor) may also find it difficult to diagnose the skin disease and may require expensive
laboratory tests to correctly identify the type and stage of the skin disease. The
advancement of lasers and photonics-based medical technology has made it possible to
diagnose skin diseases much more quickly and accurately. But the cost of such
diagnosis is still limited and very expensive. Therefore, we propose an image
processing-based approach to diagnose skin detection mobile app.
The aim of our research is to propose an efficient approach to identify skin diseases in
Sri Lanka, vitiligo and acne using image processing and machine learning. Current
research proposes an efficient approach to identify skin diseases in Sri Lanka, vitiligo
and acne. It is necessary to develop automatic methods in order to increase the accuracy
of diagnosis for skin diseases. If a person gets a skin disease, they can get the
information about those diseases from anywhere through a mobile app from anywhere.
A description of the existing skin disease can be obtained through this application.
Patients can also get minor treatments for these ailments through this app. Also, through
this application, patients can meet to a specialist of the dermatologist.
This skin diagnosis system is primarily intended to diagnose skin diseases such as acne
and vitiligo. The entire process operates under the image pre-processing, feature
extraction and classification stages. An overview of the proposed system illustrates the
process well. The process takes main elements being Image acquisition, feature
extraction and classification.
The proposed system should avoid the major difficulties encountered in diagnosing skin
diseases. Basically, building a database and integrating the dimensions of the images is
key. Different types of images are inserted as inputs, using different methods across
different models of devices. But the characteristics of those input images are different
(e.g., color and features). When the input varies, it takes a long time to process, and
storing those different images in the database can be a problem. For these reasons, no
matter what type of image is input to the proposed system, the system will resize the
image as appropriate (Image Resizing). The new image, which has been redesigned to
fit the system, is then taken to the next feature extraction stage. In the features will be
extracted from the images. After this stage, images will be entered to the classification
stage. In the classification stage, image will be classified using a machine learning
algorithm. We intend to use a supervisory machine learning algorithm for this
classification process. It is Support Vector Machine (SVM). This is a very reliable
algorithm that can be used to accurately categorize using elements extracted from the
dataset used for training. At first, images are inserted resized and edited.
Then its features are identified using a pre-trained algorithm, and finally, the machine
learning algorithm is used to identify the skin disease and finally display the identified
disease
Home
Home - image Add to Gallery And Analysis Result
Home - image add to Camera and Analysis Result
Feed -explain in Another Skin Diseases
Feed -explain in more details Another Skin Diseases
Channel - You can Channel in Srilanka Specialist of the Dermatologist.
Finally Thank You.If You have any doubts Contact me on mysite