bitphonix commited on
Commit
85c5990
·
verified ·
1 Parent(s): 8500b5e

basic update

Browse files
Files changed (1) hide show
  1. README.md +51 -40
README.md CHANGED
@@ -1,40 +1,51 @@
1
- # MediQuery - AI Multimodal Medical Assistant
2
-
3
- MediQuery is an AI-powered medical assistant that analyzes chest X-rays and answers medical queries using advanced deep learning models.
4
-
5
- ## Features
6
-
7
- - **X-ray Analysis**: Upload a chest X-ray image for AI-powered analysis
8
- - **Medical Query**: Ask questions about medical conditions, findings, and interpretations
9
- - **Visual Explanations**: View attention maps highlighting important areas in X-rays
10
- - **Comprehensive Reports**: Get detailed findings and impressions in structured format
11
-
12
- ## How to Use
13
-
14
- ### Image Analysis
15
- 1. Upload a chest X-ray image
16
- 2. Click "Analyze X-ray"
17
- 3. View the analysis results and attention map
18
-
19
- ### Text Query
20
- 1. Enter your medical question
21
- 2. Click "Submit Query"
22
- 3. Read the AI-generated response
23
-
24
- ## API Documentation
25
-
26
- This Space also provides a REST API for integration with other applications:
27
-
28
- - `POST /api/query`: Process a text query
29
- - `POST /api/analyze-image`: Analyze an X-ray image
30
- - `GET /api/health`: Check API health
31
-
32
- ## About
33
-
34
- MediQuery combines state-of-the-art image models (DenseNet/CheXNet) with medical language models (BioBERT) and a fine-tuned FLAN-T5 generator to provide accurate and informative medical assistance.
35
-
36
- Created by Tanishk Soni
37
-
38
-
39
- ---
40
- tags: [healthcare, medical, xray, radiology, multimodal]
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ title: MediQuery
3
+ emoji: 🩺
4
+ colorFrom: blue
5
+ colorTo: indigo
6
+ sdk: gradio
7
+ sdk_version: 3.36.1
8
+ app_file: app.py
9
+ pinned: false
10
+ ---
11
+
12
+ # MediQuery - AI Multimodal Medical Assistant
13
+
14
+ MediQuery is an AI-powered medical assistant that analyzes chest X-rays and answers medical queries using advanced deep learning models.
15
+
16
+ ## Features
17
+
18
+ - **X-ray Analysis**: Upload a chest X-ray image for AI-powered analysis
19
+ - **Medical Query**: Ask questions about medical conditions, findings, and interpretations
20
+ - **Visual Explanations**: View attention maps highlighting important areas in X-rays
21
+ - **Comprehensive Reports**: Get detailed findings and impressions in structured format
22
+
23
+ ## How to Use
24
+
25
+ ### Image Analysis
26
+ 1. Upload a chest X-ray image
27
+ 2. Click "Analyze X-ray"
28
+ 3. View the analysis results and attention map
29
+
30
+ ### Text Query
31
+ 1. Enter your medical question
32
+ 2. Click "Submit Query"
33
+ 3. Read the AI-generated response
34
+
35
+ ## API Documentation
36
+
37
+ This Space also provides a REST API for integration with other applications:
38
+
39
+ - `POST /api/query`: Process a text query
40
+ - `POST /api/analyze-image`: Analyze an X-ray image
41
+ - `GET /api/health`: Check API health
42
+
43
+ ## About
44
+
45
+ MediQuery combines state-of-the-art image models (DenseNet/CheXNet) with medical language models (BioBERT) and a fine-tuned FLAN-T5 generator to provide accurate and informative medical assistance.
46
+
47
+ Created by Tanishk Soni
48
+
49
+
50
+ ---
51
+ tags: [healthcare, medical, xray, radiology, multimodal]