Open-source AI model llava-dermatology-7b-v1.5-hf - Accurately assist in the diagnosis of skin diseases

Llava Dermatology 7b V1.5 Hf

Developed by Esperanto

A fine-tuned version based on the LLaVA 7B model through dermatological image transfer learning, specializing in skin disease diagnosis

Image-to-Text

Transformers

#Dermatological Image Diagnosis #LoRA Fine-tuning #Multimodal Consultation

Downloads 185

Release Time : 7/30/2024

Model Overview

This model is fine-tuned on the Skin Condition Image Network (SCIN) dataset using LoRA technology, enabling it to analyze and process images of skin conditions such as rashes and inflammations provided by users, and deliver highly accurate diagnostic recommendations.

Model Features

Specialized Dermatological Diagnosis

Optimized for skin condition images, capable of identifying various skin issues such as rashes and inflammations

LoRA Fine-tuning Technology

Utilizes LoRA technology for efficient fine-tuning, retaining the base model's capabilities while adding dermatological diagnostic expertise

Multimodal Input Processing

Capable of processing both image and text inputs, simulating real-world clinical scenarios

Model Capabilities

Skin Condition Image Analysis

Dermatological Diagnostic Recommendations

Multimodal Input Processing

Medical Q&A Interaction

Use Cases

Healthcare

Online Dermatological Diagnosis

Users upload photos of skin issues and describe symptoms to receive preliminary diagnostic recommendations

Highly accurate dermatological diagnostic recommendations

Medical Education Assistance

A supplementary tool for medical students learning dermatological diagnosis

Helps identify common skin conditions

🚀 Model Card for Model ID

This model is a fine - tuned version of LLaVA 7B on dermatology images, enabling high - accuracy skin condition diagnoses.

🚀 Quick Start

There is no specific quick - start content provided in the original document.

✨ Features

Empowers users to consult an "online dermatologist" by providing information and an image of the affected area.
Can process and analyze various skin condition images and give high - accuracy diagnoses.

📦 Installation

There is no installation step provided in the original document.

💻 Usage Examples

Basic Usage

Put the information in the demo questionnaire together and form context such as:

'This is a CLOSE UP picture of a patient's skin problem. The patient is within the age group of AGE 18 TO 29. The patient is a MALE. The patient is Hispanic Latino or Spanish Origin.  The texture of the skin problem is flat, rough or flaky.  The skin problem comes with increasing size, itching and burning symptoms. The skin problem comes with pain. The skin problem doesn't come with other symptoms. The patient's skin problem has been ONE TO FOUR WEEKS.'

Along with system prompt and user question like "Please diagnose what skin condition is most likely in the picture."

📚 Documentation

Model Details

This is a fine - tuned version of LLaVA 7B through transfer learning on Dermatology Images.

Model Description

Given the rise in demand for reliable and immediate medical advice, particularly in dermatology, this tool empowers users to consult an "online dermatologist" by providing essential information, an image of the affected area, and asking follow - up questions, closely mimicking an actual consultation.

To achieve this, we fine - tuned LLaVA 7B with LoRA on the Skin Condition Image Network (SCIN) dataset, equipping it with the ability to process and analyze user - provided images, such as rashes, inflammations, or other skin conditions, and give patients diagnoses with high accuracy.

Developed by: Esperanto Technologies
Finetuned from model: llava - hf/llava - 1.5 - 7b - hf
Blog: Updating soon

🔧 Technical Details

There is no technical detail content (more than 50 words of specific technical description) provided in the original document.

📄 License

There is no license information provided in the original document.

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