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Introducing Viteye: An AI-Driven Solution for Melanoma Detection, Diagnosis, and Direct Consultation

Hey #nostr!

I am excited to share with you our innovative approach in the field of healthcare - Viteye, a software solution that’s helping to improve the way we detect and diagnose melanoma.

We are launching our open beta testing and welcoming everyone who is interested to participate! The use of Viteye is completely free.

The Problem: Melanoma, a highly aggressive form of skin cancer, is on the rise globally. Early detection is crucial for effective treatment and improved patient outcomes, but current diagnostic methods are limited, leading to high mortality rates.

The Solution: Viteye’s AI-driven software platform uses machine learning technology to accurately diagnose melanoma by analyzing images of suspicious pigmented lesions. This approach surpasses traditional diagnostics, reducing the risk of underdiagnosis and overdiagnosis.

Since users do not generally have easy access to a dermatoscope with immersion, we have developed the lens shown in the photo, which allows Viteye users to install it on their phone and, in tandem with high-quality cameras in modern phones, enables the full potential of the model to be revealed.

The lens attachment uses two cross-polarized LEDs, which allows the obtained image to be almost identical to the image obtained using liquid immersion. The polarized light eliminates skin glare and illuminates the upper layer of skin to obtain an image of a deeper structure of the neoplasm. It also allows for clearer, more precise, and detailed examination of the colors, shapes, and textures of skin lesions.

It’s worth noting that while the use of this lens is recommended for use with the application, it’s not mandatory. Medical professionals can use the application with other types of dermatoscopes that use either immersion or cross-polarization. Photos for analysis can also be selected from the local gallery of the mobile device.

PLEASE NOTE: the model was trained on photographs taken with immersion, so using photos taken without a dermatoscope may lead to inaccurate results. For optimal accuracy, we recommend using the lens or a dermatoscope with immersion or cross-polarization capabilities.

Key Features:

* Multiplatform accessibility (Android, iPhone, laptops, PCs)

* Multilingual interface to serve a diverse user base

* Accurate melanoma detection using a machine learning model trained on thousands of histologically confirmed clinical cases (gold standard dataset).

* Direct consultation within the application for instant expert advice

* Simplified patient database management for healthcare providers

* Auto-translated chat for seamless communication between patients and doctors


Pipeline: We’re currently working on incorporating additional models trained for Kaposi’s sarcoma and basal cell carcinoma, which will be implemented in upcoming updates. This will further expand the capabilities of our platform and improve patient outcomes.


Try out the application: viteye.app

I’d love to hear your thoughts and feedback on Viteye! Let’s work together to improve melanoma detection and improve patient outcomes.

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Viteye White Paper

viteye: A Technological Vanguard in Melanoma Detection

Executive Summary

Viteye emerges as a software solution, meticulously designed to revolutionize the early detection and diagnosis of melanoma through the integration of cutting-edge artificial intelligence (AI) and machine learning technologies. This white paper delves into the escalating challenge of melanoma detection, presents the innovative approach adopted by Viteye, highlights its distinctive features, and explores its transformative potential in the healthcare landscape.

Learn more by visiting our website: 

https://vitey.ai


Introduction

The global incidence of melanoma, a highly malignant form of skin cancer, is on an upward trajectory, presenting a formidable challenge to healthcare systems worldwide. Early detection is paramount for effective treatment and improved patient outcomes, yet remains a complex problem due to the limitations of current diagnostic methods. Viteye stands at the forefront of addressing this challenge, offering a sophisticated AI-driven platform that enhances the accuracy of melanoma detection and facilitates timely intervention.

The Growing Challenge of Melanoma Detection

Melanoma is distinguished by its aggressive nature and propensity for late diagnosis, often resulting in high mortality rates. The traditional diagnostic arsenal, including visual examination and mnemonic devices like the ABCDE rule, falls short in identifying early-stage melanomas with sufficient accuracy. Moreover, the clinical presentation of early melanoma can be ambiguous, complicating the diagnostic process and underscoring the need for more advanced solutions.

viteye: A Technological Solution

At the heart of viteye is a state-of-the-art machine learning model, trained on a comprehensive dataset of clinically verified cases, enabling it to accurately diagnose melanoma by analyzing images of suspicious pigmented lesions. This approach not only surpasses the limitations of traditional diagnostics but also significantly reduces the risk of both underdiagnosis and overdiagnosis.

Key Features:

Multiplatform Accessibility: Viteye's platform is designed for universal access, supporting a wide range of devices including Android and iPhone smartphones, laptops, and PCs.

Multilingual Interface: Recognizing the global challenge melanoma presents, viteye offers a multilingual interface to serve a diverse user base.

Accurate Melanoma Detection: The core of viteye's innovation lies in its machine learning model, meticulously trained on a dataset encompassing 6,144 clinical cases with histologically verified diagnoses, ensuring unparalleled accuracy in melanoma detection.

Direct Doctor Consultation: The platform facilitates instant consultations with registered medical professionals, enabling users to seek expert advice promptly.

Database Management: viteye simplifies patient database management for healthcare providers, streamlining the registration and diagnostic process.

Auto-Translated Chat: To overcome language barriers, viteye features an auto-translated chat, ensuring seamless communication between patients and doctors from diverse linguistic backgrounds.

Scientific Foundation and Development

Viteye's development was driven by the urgent need to address the increasing global incidence of melanoma and the limitations of primary care specialists in making accurate diagnoses. The project's inception was rooted in a comprehensive understanding of melanoma's clinical challenges, as outlined by leading oncology research. The software's machine learning model was developed through rigorous training on a gold-standard dataset, ensuring its ability to deliver highly accurate diagnostic predictions.

Training and Testing

The neural network at the core of viteye underwent extensive training and testing, utilizing a dataset of 6,144 clinical cases. This process involved several stages, including the selection of the optimal neural network type, architecture, and the evaluation of the model's effecti