Mental Health Assist and Diagnosis Conversational Interface using Logistic Regression Model for Emotion and Sentiment Analysis

The aim of this work was to create a fully functional AI-ML based conversational agent that behaves like a real time therapist which analyses the user’s emotion at every step and provides appropriate responses and feedback. AI chatbots, although fairly new to the domain of mental health, can help in destigmatizing seeking help, and are more easily accessible to everyone, at any time. Chatbots provide an effective way to communicate with a user and offer helpful emotional support in a more economical way. While making regular psychiatric visits often require a fixed duration/appointment which can be time consuming and is restricted to a fraction of the day, the proposed chatbot can keep track of your health on the go at any time. The application will have a self-healing kit suggesting various exercises, both mental and physical that the user may implement in his day-to-day life. The study below goes into further detail on the major insinuations for future chatbot agent design and assessment

Dialog Development Manager

This chapter shows how software development professionals use the provided flow charts and pseudo-code to create the Dialog Development Manager. Analysts then use the Dialog Development Manager to create the problem-specific knowledge needed by a natural language processor to support the conversation between Socrates DigitalTM and end users. The Dialog Development Manager guides the analysts through design and development of the Understand, Explore, Materialize, and Realize phases to create the conversational interface for Socrates DigitalTM.

Chatbot breakthrough in the 2020s? An ethical reflection on the trend of automated consultations in health care

Many experts have emphasised that chatbots are not sufficiently mature to be able to technically diagnose patient conditions or replace the judgements of health professionals. The COVID-19 pandemic, however, has significantly increased the utilisation of health-oriented chatbots, for instance, as a conversational interface to answer questions, recommend care options, check symptoms and complete tasks such as booking appointments. In this paper, we take a proactive approach and consider how the emergence of task-oriented chatbots as partially automated consulting systems can influence clinical practices and expert–client relationships. We suggest the need for new approaches in professional ethics as the large-scale deployment of artificial intelligence may revolutionise professional decision-making and client–expert interaction in healthcare organisations. We argue that the implementation of chatbots amplifies the project of rationality and automation in clinical practice and alters traditional decision-making practices based on epistemic probability and prudence. This article contributes to the discussion on the ethical challenges posed by chatbots from the perspective of healthcare professional ethics.

Automated Emergency Room Triage: Helping Patients Get the Best Treatment

We describe an intelligent triage system for emergency rooms; the system interacts with patients and classifies them by priority level and with respect to medical specialty. The system consists of a conversational interface, coupled with sensors and a physical robot-like platform, and classifiers that operate on symptoms and measurements so as to select a medical specialty and to output a priority level. Tests with human subjects demonstrated that our Healthbot system was well received and in fact preferred to alternatives by most people. Tests have also shown that the classifiers reached accuracy consistent with a doctor's output.

Improving Access to Justice with Legal Chatbots

On average, one in three Canadians will be affected by a legal problem over a three-year period. Unfortunately, whether it is legal representation or legal advice, the very high cost of these services excludes disadvantaged and most vulnerable people, forcing them to represent themselves. For these people, accessing legal information is therefore critical. In this work, we attempt to tackle this problem by embedding legal data in a conversational interface. We introduce two dialog systems (chatbots) created to provide legal information. The first one, based on data from the Government of Canada, deals with immigration issues, while the second one informs bank employees about legal issues related to their job tasks. Both chatbots rely on various representations and classification algorithms, from mature techniques to novel advances in the field. The chatbot dedicated to immigration issues is shared with the research community as an open resource project.