AI-POWERED SKIN DIAGNOSIS AND DERMATOLOGY APPLICATION

Abstract

VISION MED: AI-POWERED SKIN DIAGNOSIS AND DERMATOLOGY APPLICATION "VISION MED" is a mobile application that utilizes artificial intelligence (AI) and image recognition technology to diagnose and manage skin conditions. Designed to enhance accessibility to dermatological care, the application allows users to capture and upload images of their skin condition, which are then analyzed by an AI-powered diagnostic module. This module detects common skin issues such as acne, eczema, psoriasis, and early signs of skin cancer, providing real-time diagnostic results and personalized treatment recommendations. The application features a telemedicine platform that enables users to schedule video consultations with dermatologists or book in-person appointments if necessary. A centralized database supports continuous data analysis, improving diagnostic accuracy over time while maintaining user privacy. Users can also track their treatment progress by uploading follow-up images, enabling ongoing assessment and adjustment of recommendations. With a user-friendly interface and strong data security measures, VISION MED offers a comprehensive, efficient, and accessible solution for skin health management, particularly benefiting users in remote or underserved areas. This invention combines the power of AI with telemedicine to make dermatological care more efficient, personalized, and widely available.

Specification

Description:VISION MED: AI-POWERED SKIN DIAGNOSIS AND DERMATOLOGY APPLICATION

FIELD OF INVENTION

[0001] The invention pertains to the field of medical diagnostics, with a particular focus on digital dermatology and telemedicine. It introduces an innovative approach to diagnosing, monitoring, and managing skin diseases through a mobile application powered by artificial intelligence (AI) and image recognition technology. The invention addresses the increasing demand for real-time, accessible, and efficient dermatological assessments and is particularly relevant for regions where specialized dermatology services are limited.

[0002] The invention leverages advances in AI algorithms, machine learning, and computer vision to accurately analyze images of skin conditions. This analysis allows for the early detection of a variety of dermatological issues, including but not limited to acne, eczema, psoriasis, alopecia areata, and potential precursors to skin cancer. The application utilizes deep learning models to detect patterns, textures, and visual markers in the images uploaded by users, providing diagnostic insights that traditionally would require in-person evaluation by a dermatologist.

[0003] By integrating telemedicine functionalities, this invention further expands the scope of dermatological care beyond conventional clinical settings. Users are provided with remote consultation options, allowing them to connect with dermatologists through video calls or in-person appointments if necessary. This feature enables users to access dermatological expertise and receive treatment recommendations without requiring immediate access to a healthcare facility.

[0004] In addition to diagnosis, the invention supports treatment planning and progress monitoring. The application provides tailored recommendations for treatment based on the diagnosed condition, with options for users to track their progress over time. This continuous monitoring aspect is particularly beneficial for chronic skin conditions that require regular observation and adjustment of treatment plans. Furthermore, the application incorporates a database for storing and analyzing user data, ensuring that insights are based on up-to-date information and can be adapted to each user's unique needs.

[0005] The invention operates at the intersection of digital health, dermatology, and AI-driven medical imaging. Its impact is particularly significant in the realm of tele dermatology, where it enhances access to quality dermatological care, reduces diagnostic delays, and offers an efficient solution for underserved populations. Through the use of AI, the application not only aids in early disease detection but also provides personalized recommendations, enabling users to take proactive steps toward managing their skin health. The integration of data processing and real-time connectivity with a central server ensures a reliable and secure user experience, where diagnostic accuracy and data privacy are paramount.

[0006] In summary, this invention falls within the broader domain of AI-based diagnostic technologies and telehealth solutions, specifically in the application of skin health management. It advances the current state of dermatological care by combining image recognition with AI-driven diagnostics, telemedicine, and continuous data analysis to offer a holistic, accessible, and efficient solution for skin disease management.

BACKGROUND OF THE INVENTION

[0007] Skin diseases are among the most common health concerns worldwide, affecting individuals across all age groups and demographics. Conditions such as acne, eczema, psoriasis, and alopecia areata not only impact physical health but also contribute to significant emotional and psychological distress. Early and accurate diagnosis is critical for managing these conditions effectively, yet many individuals, especially those in remote or underserved areas, have limited access to dermatological expertise. Traditional diagnostic processes often involve in-person visits, long waiting times, and repeated consultations, which can delay treatment initiation and increase healthcare costs.

[0008] With the rise of telemedicine and digital health technologies, there has been a growing demand for solutions that allow patients to access healthcare remotely. The COVID-19 pandemic accelerated this demand, highlighting the need for efficient, contactless healthcare options. However, existing telemedicine solutions often lack specific tools for real-time, accurate, and user-friendly dermatological assessments. Furthermore, even though dermatology is a visual specialty that can benefit significantly from image-based assessments, the use of artificial intelligence (AI) for image analysis in this field remains underdeveloped in many telehealth applications.

[0009] Advances in AI, machine learning, and image processing now make it possible to create systems that can automatically analyze skin conditions based on user-submitted images, potentially enabling early detection of serious skin diseases, reducing misdiagnoses, and offering personalized treatment suggestions. However, while AI-powered diagnostic tools have shown promise, many existing models are limited by their lack of integration with telemedicine platforms, poor accessibility, or insufficient accuracy for practical use in diverse populations.

[0010] "VISION MED" addresses these limitations by combining AI-powered image recognition with a comprehensive tele dermatology platform designed specifically for skin health. This invention is built to provide accurate, real-time analysis of skin conditions, enabling users to self-assess and manage their skin health more effectively. By leveraging AI algorithms that analyze images to detect patterns, colors, and textures associated with various skin diseases, "VISION MED" offers a non-invasive, cost-effective, and accessible diagnostic tool for the general population.

[0011] Furthermore, the application goes beyond basic diagnosis by integrating treatment planning, personalized recommendations, and remote consultation options. Users can receive a suggested treatment plan based on their condition, track their progress over time, and consult with dermatologists via video call or in-person appointments if needed. This flexibility and accessibility make "VISION MED" a valuable tool for individuals in remote areas or those who lack immediate access to dermatological care.

[0012] In addition, the application's database and continuous data processing capabilities allow it to refine its diagnostic accuracy over time and provide up-to-date recommendations. By storing data on skin conditions and treatment outcomes, the application can leverage AI-driven insights to improve diagnostic precision and adapt to evolving medical knowledge.

[0013] In conclusion, "VISION MED" responds to the growing need for accessible, accurate, and timely dermatological care. It enables users to manage their skin health independently while also facilitating professional consultations when necessary. By integrating AI with tele dermatology, this invention represents a significant advancement in digital health, offering a practical, scalable solution to improve dermatological outcomes and extend care to underserved populations.

[0014] 202231004658: The invention introduces a handheld dermoscopic tool designed for the diagnosis of skin diseases, particularly skin cancer, which has become more prevalent due to increased pollution and ozone depletion. Early detection of skin cancer, especially melanoma, is crucial for improving survival rates. The proposed tool offers a quick, easy-to-use, and accurate system that enables home diagnosis and educates the public about skin conditions and their effects. By facilitating early detection, this device has the potential to save thousands of lives, marking a significant advancement in smartphone-based diagnostics.

[0015] 202441038034: Early detection and diagnosis of skin diseases are vital for improved health outcomes. Identifying skin conditions at their initial stages allows healthcare professionals to intervene promptly, reducing the risk of disease progression and complications. This is especially critical for skin cancers, where early detection greatly increases treatment success rates. Timely diagnosis also enables effective management strategies, alleviating discomfort and enhancing quality of life. Overall, early detection is a key aspect of preventive medicine, promoting timely intervention and supporting better health results.

[0016] 202421019840: The "Computer-Aided Diagnosis System for Skin Disease Identification" addresses the challenges of diagnosing diverse skin diseases by offering an automated solution to support dermatologists. This advanced CAD system utilizes machine learning and image processing to analyze high-resolution skin lesion images for accurate diagnostic support. It begins with image acquisition and preprocessing to enhance quality, followed by feature extraction of color, texture, shape, and size. These features are analyzed by deep neural networks to classify skin conditions. Trained on extensive datasets, the system achieves high accuracy and provides possible diagnoses with confidence scores. Its user-friendly interface allows seamless interaction, image annotation, diagnostic result visualization, and integration with electronic health records. The CAD system continuously improves through clinician feedback and updates, making it a powerful tool in dermatology.

OBJECTS OF THE INVENTION

[0017] The invention primarily aims to:

[0018] Use AI-powered image analysis for early diagnosis of skin conditions, including acne, eczema, and potential skin cancers.

[0019] Provide a mobile-based dermatology solution for remote and underserved areas, reducing barriers to care.

[0020] Offer tailored treatment recommendations and monitor progress to adapt care based on user data.

[0021] Integrate video and in-person appointment options to connect users with dermatologists as needed.

[0022] Maintain a database to refine diagnostic algorithms and increase precision over time.

[0023] Feature an intuitive interface that allows users to easily capture images, receive results, and understand recommendations.

[0024] Collect anonymized data to contribute to dermatological research and insights on skin health trends.

[0025] Encourage proactive monitoring of skin health to prevent progression of conditions.

[0026] Implement strong data security and privacy measures to safeguard health information.

SUMMARY OF THE INVENTION

[0027] The invention, "VISION MED," is an AI-driven mobile application designed to provide real-time diagnosis and management of skin conditions. It leverages advanced image recognition and machine learning algorithms to analyze user-uploaded images, enabling the early detection of skin diseases such as acne, eczema, psoriasis, alopecia areata, and potential precursors to skin cancer. By offering users an accessible, efficient, and accurate tool for diagnosing skin conditions, the application addresses significant gaps in dermatological care, particularly for those in remote or underserved areas.

[0028] VISION MED provides personalized treatment recommendations and monitors user progress over time, adapting its suggestions based on individual responses. Users can connect with dermatologists through built-in telemedicine options, allowing both video and in-person consultations when necessary. The application's centralized database supports continuous data analysis, enhancing diagnostic accuracy and providing up-to-date, data-driven insights.

[0029] The user-friendly interface ensures that individuals, regardless of medical background, can easily capture images, interpret results, and make informed decisions about their skin health. Additionally, VISION MED emphasizes data security, implementing privacy measures to protect user information.

[0030] In summary, "VISION MED" is a comprehensive dermatology tool that combines AI diagnostics, telemedicine, and personalized care to empower users in managing their skin health and to improve access to timely, high-quality dermatological services.

BRIEF DESCRIPTION OF DRAWING

[0031] The figure 1 is a workflow diagram illustrating the process flow of the "VISION MED" application.

[0032] The figure 2 is the flowchart illustrates the step-by-step workflow of the "VISION MED" application, detailing the user journey from initial engagement to diagnosis, consultation, and treatment.

DETAILED DESCRIPTION OF THE INVENTION

[0033] The present invention, "VISION MED," is a mobile application that leverages artificial intelligence (AI) and image recognition technology to diagnose, monitor, and provide treatment recommendations for various skin conditions. It addresses the need for accessible dermatological care, especially for individuals in remote or underserved areas, by offering a reliable tool for skin disease detection and telemedicine support.

[0034] System Overview- The VISION MED application consists of multiple integrated components designed to streamline the diagnostic process, improve accuracy, and enhance user experience. Key components include:

[0035] User Interface (UI): The app's UI is designed for ease of use, allowing individuals to upload images of their skin condition with minimal steps. It also provides access to diagnosis results, treatment recommendations, and consultation options.

[0036] AI-Powered Diagnostic Module: The core of the invention, this module uses machine learning algorithms and image recognition technology to analyze images of skin conditions, identify patterns and features, and make accurate diagnoses based on known dermatological markers.
[0037] Database and Data Processing Server: A backend server stores and processes images and diagnostic data, maintaining a repository of information on various skin conditions. The database is regularly updated to reflect advances in dermatological knowledge, enhancing diagnostic accuracy over time.

[0038] Operation and Workflow- The VISION MED workflow begins with the user (patient) launching the application and following these primary steps:

[0039] Profile Setup: The user creates a profile and inputs relevant information, such as age, skin type, and any known skin conditions, which can help refine diagnosis and treatment recommendations.

[0040] Image Capture and Diagnosis: The user takes a photo of the affected skin area using their smartphone's camera.

[0041] This image is processed by the AI diagnostic module, which analyzes the image for visual markers associated with skin conditions such as acne, eczema, psoriasis, alopecia areata, and potential precursors to skin cancer.

[0042] The diagnostic module uses a combination of machine learning techniques to compare the image with a large dataset of known skin conditions, identifying characteristic patterns like color, texture, shape, and distribution of skin lesions.

[0043] Database Querying and Reference: After initial analysis, the system queries the central database to cross-reference findings with existing medical data on skin conditions.

[0044] The database stores detailed information on various skin diseases, including symptoms, progression, and typical appearances, which aids in refining the diagnosis and minimizing errors.

[0045] Based on this data, the app presents a diagnosis report to the user with a confidence level, explaining the likely skin condition and suggested treatment options.
[0046] Treatment Recommendations: If the diagnostic result indicates a mild or common condition, the app provides personalized treatment recommendations. This may include topical medications, skincare routines, and general advice based on the diagnosis.

[0047] For chronic or severe conditions, the app suggests consulting a dermatologist. Recommendations are adapted over time based on user feedback, treatment outcomes, and updated medical data.

[0048] Consultation and Telemedicine Integration- VISION MED incorporates a telemedicine platform that connects users with licensed dermatologists for further consultation if needed. This feature includes:

[0049] Remote Video Consultation: The app provides the option for users to schedule a video call with a dermatologist. During the call, the dermatologist can review the user's images and diagnosis report and provide expert advice or further treatment recommendations.

[0050] In-Person Appointment Booking: If an in-depth examination is necessary, the app allows users to book in-person appointments with nearby dermatologists. This feature is integrated with a location-based service to help users find available healthcare providers within their area.

[0051] Progress Monitoring and Continuous Support- The application is designed to support users throughout the treatment and recovery phases by offering progress monitoring and follow-up reminders:

[0052] Tracking Treatment Effectiveness: Users can update the app with new images at intervals to track the progress of their skin condition. The AI module compares new images with previous ones, helping users and dermatologists assess treatment effectiveness and make adjustments as necessary.

[0053] Customized Alerts and Reminders:- The app sends reminders for follow-up assessments and provides alerts for any changes detected in the user's condition that may require immediate attention.

[0054] Data Security and Privacy- The VISION MED application prioritizes user data privacy and complies with relevant healthcare data protection standards. Key measures include:

[0055] Data Encryption: All user data, including images, personal information, and diagnostic records, are encrypted to ensure privacy.

[0056] Secure Data Storage: Diagnostic data and treatment history are stored on secure servers, with controlled access to ensure data integrity and prevent unauthorized access.

[0057] Anonymized Data for Research: The application anonymizes collected data to contribute to dermatological research, allowing patterns and insights to be extracted for improving diagnostic accuracy without compromising user privacy.

[0058] Technical Implementation- AI and Machine Learning Algorithms: The invention utilizes convolutional neural networks (CNNs) and other machine learning models to identify dermatological patterns. These algorithms are trained on large datasets of skin condition images, allowing the system to recognize complex visual features associated with different skin diseases.

[0059] Image Preprocessing and Enhancement: The app includes image preprocessing capabilities to enhance clarity, reduce noise, and standardize images, ensuring consistency in analysis and improving diagnostic accuracy.

[0060] Database Management System (DBMS): The backend database is designed for scalability, with the ability to accommodate a growing repository of dermatological data and improve accuracy through continuous learning and updates.

[0061] Applications and Use Cases- The VISION MED application can be utilized in a variety of contexts, including:
[0062] Personal Health Management: For individuals seeking to monitor and manage their skin health independently.

[0063] Primary Care Support: As a diagnostic tool for primary care providers to quickly assess skin conditions before referring to a specialist.

[0064] Dermatology Clinics: Offering an efficient pre-diagnostic tool to screen patients, saving time and resources for dermatologists.
, Claims:We claim:

Claim 1: A mobile application for diagnosing skin conditions, comprising:
• An image capture module configured to receive images of a user's skin condition;
• An AI-powered diagnostic module that analyzes the captured images using image recognition algorithms to identify potential skin conditions based on characteristic patterns;
• A database containing information on various skin conditions, cross-referenced with the diagnostic module to improve accuracy;
• A user interface displaying diagnostic results and recommended treatment options to the user.

Claim 2: The application of Claim 1, wherein the AI-powered diagnostic module utilizes machine learning algorithms and a convolutional neural network (CNN) trained on a dataset of skin condition images for enhanced diagnostic accuracy.

Claim 3: The application of Claim 1, further comprising a treatment recommendation module that provides personalized treatment suggestions based on the diagnosed condition, including over-the-counter medications, skincare advice, and lifestyle recommendations.

Claim 4: The application of Claim 1, further comprising a telemedicine module that enables remote consultations, allowing users to:
• Schedule video consultations with dermatologists;
• Book in-person appointments with nearby healthcare providers based on the user's location.

Claim 5: The application of Claim 1, further comprising a progress monitoring module that allows users to upload follow-up images over time, tracking changes in their skin condition and adjusting recommendations based on the progression.

Claim 6: The application of Claim 1, wherein the database is designed to store and analyze anonymized data for continuous improvement of diagnostic algorithms and to contribute insights for dermatological research.

Claim 7: The application of Claim 1, further comprising security protocols to ensure data privacy, including:
• Data encryption for user images and personal health information;
• Secure storage on a centralized server with restricted access;
• Compliance with healthcare data protection regulations to maintain confidentiality.

Claim 8: A method for diagnosing and managing skin conditions using a mobile application, comprising:
• Capturing an image of a skin condition;
• Processing the image with an AI diagnostic module to identify visual markers and probable conditions;
• Cross-referencing the diagnostic result with a database of known skin conditions;
• Displaying the diagnostic result and recommended treatment options to the user.

Claim 9: The method of Claim 8, further comprising a feedback mechanism that adjusts future recommendations based on user feedback and outcomes from prior treatments, enhancing the personalization and accuracy of the treatment plan.

Claim 10: The application of Claim 1, further comprising an alert system that notifies the user when the analysis detects conditions that require urgent medical attention, prompting immediate consultation options.

Documents