Empathia AI is an innovative AI-powered charting assistant designed for healthcare professionals. It streamlines the process of transcribing patient encounters and automatically generating charts, allowing clinicians to focus more on patient care. This tool significantly reduces the time spent on administrative tasks, enhances accuracy in documentation, and ensures patient data security through HIPAA-compliant encryption.
Empathy AI
A medical assistant for primary care physicians, transcribes patient visits and automatically creates medical records, improving patient care and service.
Introduction
Feature
Time-Saving Transcription
Empathia AI dramatically reduces the hours clinicians spend on charting, allowing them to allocate more time to patient care.
Seamless EMR Integration
The platform enables easy copying and pasting of notes from a single browser tab, integrating smoothly with existing Electronic Medical Record systems.
High Accuracy and Precision
Empathia AI ensures that all crucial details of patient encounters are captured accurately, maintaining the integrity of medical records.
Versatile Application
The tool supports both telemedicine and multilingual patient encounters, providing instant, high-quality chart creation regardless of the consultation format or language.
User-Friendly Interface
Empathia AI operates directly from your browser with a simple click-to-start and click-to-stop functionality, making it effortless to use.
HIPAA-Compliant Security
All patient data is stored securely with HIPAA-compliant encryption, guaranteeing privacy and security of sensitive medical information.
FAQ
What is Empathia AI?
Empathia AI is an AI-powered charting assistant that transcribes patient encounters and automatically generates charts, freeing clinicians from note-taking to focus more on patient care.
How does Empathia AI work?
Users can utilize Empathia AI's charting assistant to transcribe patient encounters and automatically generate charts. The process is simple: start the recording at the beginning of the encounter and stop it at the end. The AI then processes the information and generates a comprehensive chart.
Can Empathia AI generate images?
No, Empathia AI is a text-based charting assistant and does not have image generation capabilities.
Does Empathia AI offer GPTs?
Empathia AI does not have GPTs available. It is specifically designed as a text-based charting assistant for transcribing patient encounters and generating charts.
How can I maximize the use of Empathia AI?
Users can maximize their use of Empathia AI by leveraging the daily free uses of the charting assistant to explore its AI-powered tools for various tasks related to patient documentation.
Will my data be used for training purposes?
No, Empathia AI values user privacy highly. Your data will not be used for any training purposes. Users can delete their account at any time, which will remove all associated data.
When should I consider an Empathia AI subscription?
If the free version of Empathia AI doesn't meet your needs and you heavily rely on its charting assistant, subscribing to their affordable products might be beneficial.
Latest Traffic Insights
Monthly Visits
193.90 M
Bounce Rate
56.27%
Pages Per Visit
2.71
Time on Site(s)
115.91
Global Rank
-
Country Rank
-
Recent Visits
Traffic Sources
- Social Media:0.48%
- Paid Referrals:0.55%
- Email:0.15%
- Referrals:12.81%
- Search Engines:16.21%
- Direct:69.81%
Related Websites
Midjourney SREF Codes Library for Style Reference What are SREF Codes? SREF codes are special text strings used in Midjourney to quickly and easily apply specific artistic styles to your image generations. How to Use SREF Codes: Simply add an SREF code to your Midjourney prompt. For example: `/imagine a majestic dragon, SREF:cyberpunk` SREF Code Library: This library contains a collection of SREF codes categorized by style. * Art Styles: * `photorealistic`: Creates images with high levels of realism. * `impressionistic`: Captures the essence of a scene with loose brushstrokes and vibrant colors. * `cubist`: Breaks down objects into geometric shapes. * `surrealist`: Creates dreamlike and fantastical images. * `abstract`: Focuses on form, color, and composition rather than representational imagery. * Visual Effects: * `cinematic`: Gives images a cinematic look and feel. * `HDR`: Creates images with high dynamic range, resulting in greater detail and contrast. * `neon`: Adds vibrant neon lights to the image. * `pixel art`: Generates images in a retro pixel art style. * Other Styles: * `anime`: Creates images in the style of Japanese animation. * `manga`: Similar to anime, but with a more comic book aesthetic. * `sketch`: Generates images that resemble pencil sketches. * `watercolor`: Creates images with the look and feel of watercolor paintings. Note: This is just a small sample of the many SREF codes available. Explore and Experiment: The best way to learn about SREF codes is to experiment with them! Try combining different codes to create unique and interesting styles.
Midjourney SREF Codes Library for Style Reference What are SREF Codes? SREF codes are special text strings used in Midjourney to quickly and easily apply specific artistic styles to your image generations. How to Use SREF Codes: Simply add an SREF code to your Midjourney prompt. For example: `/imagine a majestic dragon, SREF:cyberpunk` SREF Code Library: This library contains a collection of SREF codes categorized by style. * Art Styles: * `photorealistic`: Creates images with high levels of realism. * `impressionistic`: Captures the essence of a scene with loose brushstrokes and vibrant colors. * `cubist`: Breaks down objects into geometric shapes. * `surrealist`: Creates dreamlike and fantastical images. * `abstract`: Focuses on form, color, and composition rather than representational imagery. * Visual Effects: * `cinematic`: Gives images a cinematic look and feel. * `HDR`: Creates images with high dynamic range, resulting in greater detail and contrast. * `neon`: Adds vibrant neon lights to the image. * `pixel art`: Generates images in a retro pixel art style. * Other Styles: * `anime`: Creates images in the style of Japanese animation. * `manga`: Similar to anime, but with a more comic book aesthetic. * `sketch`: Generates images that resemble pencil sketches. * `watercolor`: Creates images with the look and feel of watercolor paintings. Note: This is just a small sample of the many SREF codes available. Explore and Experiment: The best way to learn about SREF codes is to experiment with them! Try combining different codes to create unique and interesting styles.Explore a list of 177 unique Midjourney sref codes and style references to find your perfect Midjourney sref code effect.
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* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`
Method 2: Google Apps Script
* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`
Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.](https://static.right-ai.com/tools/2024/7/3/chromewebstore-google-com-detail-chatgpt-for-google-for-fr-pabeminldebomngnkgffiejipjjaaogi-thumbnail-1720037311.png "Get ChatGPT for Free with Google
You can now access ChatGPT, a powerful language model, for free with Google. Here's how:
Method 1: Google Colab
* Open Google Colab ([colab.research.google.com](http://colab.research.google.com))
* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = \"Your input here\"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`
Method 2: Google Apps Script
* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = \"Your input here\"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`
Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.")
Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.
Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.How to Add ChatGPT to All Google Searches ===================================================== Step 1: Create a Custom Search Engine -------------------------------------- * Go to the [Google Custom Search Engine](https://cse.google.com/) website and sign in with your Google account. * Click on the "New Search Engine" button. * Fill in the required information, such as the name and description of your search engine. * Click on the "Create" button. Step 2: Add ChatGPT to the Search Engine ----------------------------------------- * In the "Setup" tab, click on the "Add" button next to "Sites to search". * Enter the following URL: `https://chat.openai.com/` * Click on the "Add" button. Step 3: Configure the Search Engine -------------------------------------- * In the "Setup" tab, click on the "Edit" button next to "Search engine keywords". * Add the following keywords: `ChatGPT` * Click on the "Save" button. Step 4: Get the Search Engine Code ------------------------------------- * In the "Setup" tab, click on the "Get code" button. * Copy the HTML code provided. Step 5: Add the Search Engine to Your Browser ------------------------------------------------ * Open your browser and go to the "Settings" or "Options" page. * Look for the "Search engine" or "Default search engine" option. * Click on the "Add" or "Manage search engines" button. * Paste the HTML code you copied earlier. * Click on the "Add" or "Save" button. You're Done! =============== Now, whenever you search on Google, ChatGPT will be included in the search results. You can also use the custom search engine URL provided by Google to search directly.
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