AI-Powered chatbot for health industry
Because our conversational chatbot is not pre-scripted and is not rule-based, its content is not outdated. It has the most recent information available. It can quickly cross-correlate data, called “transfer learning”, to determine for example any adverse effects in using a combination of several types of medicine. It can research the vast amount of data available on the web to understand use cases. It can find what treatments worked in what cases, and which ones did not yield the desired outcome.
Doctellu is a Human Like Chatbots
Our product is a conversational human-like chatbot that will assist users with their medical and health-related questions.
DOCTELLU IS A Chatbot Using Deep learning
We will develop a conversational chatbot using Deep Learning (DL) techniques (a branch of Machine Learning) and then run it on a cloud server.
DOCTELLU IS A CHATBOT with learning ability
A learning experience is provided and neural connections are made (the learning). Then, new experiences are introduced. Artificial Intelligence (AI) will decide based on previous learning.
DOCTELLU IS A usable in websites and apps
The product can be a standalone chatbot used by businesses appearing on the business’s website, Apps or connected to the business “help-line” telephone numbers.
DOCTELLU IS A is hosted on on cloud servers
We can host it ourselves or pay another company such as Amazon or Microsoft to host it on our behalf. The software will be written in Python will run on the server.
DOCTELLU IS A CHATBOT learns continuously
Any new experience provides a new learning opportunity allowing the AI using ANN to make more accurate decisions by analyzing the current question (issue) relative to past learning.
DOCTELLU IS A text based AI powered chatbot
It is designed to interact with humans through the textual conversation process and is integrated with various messaging services and personal assistance thereby assisting users in various sectors.
DOCTELLU learns from human to human conversations
A cognitive chatbot uses the combinations of Natural Language Processing and Recurrent Neural Networks (RNN). It learns from human to human conversations.
DOCTELLU will provide accurate suggestions
With the permission of a patient, the chatbot can update the HCP on a regular basis on progress the patient. Thus, supporting preventative measures which will ultimately result in an overall lower cost of total healthcare management while potentially improving a patient’s quality of life.
Industries
We Serve a Variety of Businesses & Industries
Our chatbot can easily accomplish what companies like WebMD does and much more due to its machine learning (ML) capability using what is called a Recurrent Neural Network (RNN).
We use artificial intelligence technology techniques to interact with humans through the textual conversation process and is integrated with various messaging services and personal assistance thereby assisting users in various conversational scenarios.
Long short-term memory (LSTM) is an artificial recurrent neural network architecture used in the field of deep learning. Unlike standard feedforward neural networks, LSTM has feedback connections. It can not only process single data points, but also entire sequences of data. As an example, an LSTM can predict a word in a sequence of words to complete a sentence.
In a bidirectional LSTM which is an extension of traditional LSTM, the prediction of the missing word (in the previous example) is improved by looking backward in time on that conversation to learn about any consequence of the action described in the first sentence with a missing word. As applicable to our case, the ML will learn about the questions that led to certain answers, and separately the ML will lean about the answers that were offered to certain questions. In this way, the learning is bidirectional; hence improves the accuracy of the answers provided.
Online Stores
Health Care
Government
Softwares
Contact Us
(431) 400-4291
300-136 Market Street. Winnipeg, Manitoba R3B 0P4
Monday-Friday: 8am – 5pm
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