Virtual Telemedicine Using Natural Language Processing

2010 ◽  
Vol 5 (1) ◽  
pp. 43-55 ◽  
Author(s):  
Imran Sarwar Bajwa
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
The Other ◽  
Time Constraints ◽  
Medical Specialist ◽  
Medical Expert ◽  
Long Distance ◽  
Remote Areas ◽  
Medical Facilities ◽  
Long Time

Conventional telemedicine has limitations due to the existing time constraints in the response of a medical specialist. One major reason is that telemedicine based medical facilities are subject to the availability of a medical expert and telecommunication facilities. On the other hand, communication using telecommunication is only possible on fixed and appointed time. Typically, the field of telemedicine exists in both medical and telecommunication areas to provide medical facilities over a long distance, especially in remote areas. In this article, the authors present a solution for ‘virtual telemedicine’ to cope with the problem of the long time constraints in conventional telemedicine. Virtual Telemedicine is the use of telemedicine with the methods of artificial intelligence.

scholarly journals Mood and force in defeasible arguments

2021 ◽  
pp. 1-26
Author(s):  
Ryan Phillip Quandt ◽  
John Licato
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Word Meaning ◽  
The Other ◽  
Argumentation Schemes ◽  
Easy Task ◽  
Critical Questions ◽  
Grammatical Mood ◽  
The Moment ◽  
Precise Theory

Argumentation schemes bring artificial intelligence into day to day conversation. Interpreting the force of an utterance, be it an assertion, command, or question, remains a task for achieving this goal. But it is not an easy task. An interpretation of force depends on a speaker’s use of words for a hearer at the moment of utterance. Ascribing force relies on grammatical mood, though not in a straightforward or regular way. We face a dilemma: on one hand, deciding force requires an understanding of the speaker’s words; on the other hand, word meaning may shift given the force in which the words are spoken. A precise theory of how mood and force relate helps us handle this dilemma, which, if met, expands the use of argumentation schemes in language processing. Yet, as our analysis shows, force is an inconstant variable, one that contributes to a scheme’s defeasibility. We propose using critical questions to help us decide the force of utterances.

scholarly journals AI Chatbot Design during an Epidemic like the Novel Coronavirus

Healthcare ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 154 ◽  
Author(s):  
Gopi Battineni ◽  
Nalini Chintalapudi ◽  
Francesco Amenta
Keyword(s):  
Artificial Intelligence ◽  
Preventive Measures ◽  
Diagnostic Evaluation ◽  
The Novel ◽  
Healthcare Staff ◽  
Medical Specialist ◽  
Remote Areas ◽  
Global Pandemic ◽  
Novel Coronavirus

Since the discovery of the Coronavirus (nCOV-19), it has become a global pandemic. At the same time, it has been a great challenge to hospitals or healthcare staff to manage the flow of the high number of cases. Especially in remote areas, it is becoming more difficult to consult a medical specialist when the immediate hit of the epidemic has occurred. Thus, it becomes obvious that if effectively designed and deployed chatbot can help patients living in remote areas by promoting preventive measures, virus updates, and reducing psychological damage caused by isolation and fear. This study presents the design of a sophisticated artificial intelligence (AI) chatbot for the purpose of diagnostic evaluation and recommending immediate measures when patients are exposed to nCOV-19. In addition, presenting a virtual assistant can also measure the infection severity and connects with registered doctors when symptoms become serious.

Exploring the Possibility of Using TV White Spaces in Africa

2018 ◽  
pp. 47-71
Author(s):  
Benny Nyambo ◽  
Benard Mapako ◽  
Michael Munyaradzi
Keyword(s):  
Poverty Reduction ◽  
Internet Access ◽  
The Other ◽  
Band Spectrum ◽  
Long Distance ◽  
Mobile Data ◽  
Remote Areas ◽  
Tv White Spaces ◽  
White Spaces ◽  
The People

The people living in remote parts of the underdeveloped world usually do not have access to affordable internet, either because it is too expensive to lay fibre to these areas or mobile data is just too expensive to use every day. There has always been a need to find a way to bring fast, cheap, and reliable internet access to these people. This is where the TV white spaces (TVWS) or unused TV band spectrum comes in. TVWS refers to the gaps found between TV channels. It can be used to provide cheaper and reliable broadband to remote areas. Wi-Fi typically covers short distances and has trouble passing through obstacles. TVWS, on the other hand, can travel long distances and can penetrate obstacles. This makes TVWS suitable for long distance internet provision in remote areas. This chapter explores the possibilities and advantages of delivering broadband to remote areas of underdeveloped nations using TVWS with the intention of poverty reduction. The concept of TV channels digitalization also frees the whole analogue TV spectrum and allows it to be used in TVWS technology.

scholarly journals Medical Specialty Recommendations by an Artificial Intelligence Chatbot on a Smartphone: Development and Deployment (Preprint)

2021 ◽  
Author(s):  
Hyeonhoon Lee ◽  
Jaehyun Kang ◽  
Jonghyeon Yeo
Keyword(s):  
Artificial Intelligence ◽  
Primary Care ◽  
Deep Learning ◽  
Language Processing ◽  
Web Application ◽  
Medical Specialty ◽  
Primary Care Providers ◽  
Contactless Method ◽  
Care Providers ◽  
Medical Specialist

BACKGROUND The current coronavirus disease 2019 (COVID-19) pandemic limits daily activities, even contact between patients and primary care providers. This makes it more difficult to provide adequate primary care services, which include connecting patients to an appropriate medical specialist. A smartphone-compatible AI chatbot that classifies patients’ symptoms and recommends the appropriate medical specialty could provide a valuable solution. OBJECTIVE In order to establish a contactless method of recommending the appropriate medical specialty, this study aims to construct a deep learning-based natural language processing (NLP) pipeline and to develop an artificial intelligence (AI) chatbot that can be used on a smartphone. METHODS We collected 118,008 sentences containing information on symptoms with labels (medical specialty), conducted data cleansing, and finally constructed a pipeline of 51,134 sentences for this study. Several deep learning models, including four different Long Short-Term Memory (LSTM) models with or without attention and with or without a pretrained FastText embedding layer as well as Bidirectional Encoder Representations from Transformers (BERT) for NLP, were trained and validated using a randomly selected test dataset. The performance of the models was evaluated by the precision, recall, F1 score and area under the receiver operating characteristic curve (AUC). An AI chatbot was also designed to make it easy for patients to use this recommendation system. We used an open-source framework called Alpha to develop our AI chatbot. This takes the form of a web application with a frontend chat interface capable of conversing in text and a backend cloud-based server application to handle data collection, process the data with a deep learning model, and offer the medical specialty recommendation in a responsive web which is compatible with both desktops and smartphones. RESULTS The BERT model yielded the best performance, with an AUC of 0.964 and F1 score of 0.768, followed by LSTM with embedding vectors, with an AUC of 0.965 and F1 score of 0.739. Considering the limitations of computing resources and the wide availability of smartphones, the LSTM model with embedding vectors trained on our dataset was adopted for our AI chatbot service. We also deployed an Alpha version of the AI chatbot to be executed on both desktops and smartphones. CONCLUSIONS With the increasing need for telemedicine during the current COVID-19 pandemic, an AI chatbot based on a deep learning-based NLP model that can recommend a medical specialty to patients using their smartphones would be exceedingly useful. The chatbot allows patients to quickly and contactlessly identify the proper medical specialist based on their symptoms, and so may support both patients and primary care providers.

scholarly journals AI Based Student Bot for Academic Information System using Machine Learning

2019 ◽  
pp. 590-596
Author(s):  
Vijayakumar R ◽  
Bhuvaneshwari B ◽  
Adith S ◽  
Deepika M
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Python Language ◽  
Time Period ◽  
Long Time ◽  
Academic Information ◽  
Chat Bot

In General all the institutions like colleges sends their notes and information to students individually. Sometimes the student can�t access it quickly and repetition of data also increased. The realm of this work is to create a Chatbot for the college purpose. Our work reduces the human work to send every details and notes to all departments by email or some other medium. In this work, academic information's /details feed it to the database which will be available for the long time period. The academic information consists of information about placements details, exam time tables, semester notes and upcoming events. A Chatbot is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods. The chat bot stores the data by key words and when the user entered data is matched with the key it reply the assigned data for it. The Chatbot is created by using python language and Natural language processing. This project make use of the MySQL database to store the information. With the help of natural language processing the bot AI understand the message sent by the user and reply with the matched key value. In this Chatbot the user first need to login by their college roll number and Department. When the valid person asks about the particular information by text the information gets retrieved from the updated database that related to their department. Through this chat box the student can easily access whenever they want and the data need not to be update more than once.

Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 67-78
Author(s):  
Guy Barash ◽  
Mauricio Castillo-Effen ◽  
Niyati Chhaya ◽  
Peter Clark ◽  
Huáscar Espinoza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cyber Security ◽  
Question Answering ◽  
Intent Recognition ◽  
Affective Content ◽  
Learning Plan ◽  
Dialog System ◽  
Affective Content Analysis ◽  
Games And Simulations

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.

Leading with Pedagogical Tact- a Challenge in Children's Sports in Sweden

2010 ◽  
Vol 19 (1-2) ◽  
pp. 127-147 ◽  
Author(s):  
Krister Hertting
Keyword(s):  
Daily Activity ◽  
The Other ◽  
Competitive Sport ◽  
Sports Clubs ◽  
Youth Politics ◽  
Pedagogical Tact ◽  
Children And Parents ◽  
Swedish Society ◽  
Long Time ◽  
Voluntary Commitment

Leading with Pedagogical Tact- a Challenge in Children's Sports in Sweden The purpose of this article is to elucidate and problemize meetings between children and leaders in children's sport. The competitive sport is high valuated in the Swedish society and sport for children is central in the Swedish youth politics. The foundation in Swedish sport, as well as in the other Nordic countries, has for a long time relied on voluntary commitment. Approximately 650 000 people are voluntary engaged as leaders in sport in Sweden and 70% of children between 7 and 14 years compete in sports clubs. There is, however, a tension in the Swedish sport system. The sports for children has double missions - ‘association nurturing’ and ‘competition nurturing’, missions which are not always in harmony. In the daily activity it is the voluntary leaders who have to deal with these missions, which creates a field of tension. In this article I argue for a bridge between these missions by a leadership based on pedagogical tact. The empirical outlook is a narrative based on statements from leaders, children and parents in a study dealing with voluntary leadership within children's football. In the end I argue that focusing on this bridge is a win-win situation, both for children and sports.

DEVELOPING THE SCIENTIFIC MAGAZINE IN THE PERIOD OF THE FOURTH INDUSTRIAL REVOLUTION 4.0

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Nguyen Duy Dung
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Industrial Revolution ◽  
Scientific Journal ◽  
Publishing Research ◽  
The Other ◽  
High Tech ◽  
Fourth Industrial Revolution ◽  
Socio Economic Development ◽  
International Scientific Journal

Characteristics of the industrial revolution 4.0 is the wide application of high-tech achievements, especially information technology, digitalization, artificial intelligence, network connections for management to create sudden changes in socio-economic development of many countries. Therefore, to reach the high-tech time, many magazines in Vietnam have changed dramatically, striving to reach the international scientific journal system of ISI, Scopus. The publication of international standard scientific journal will meet the demand of publishing research results of local scientists, on the other hand contribute to strengthening exchange, cooperation, international integration in science and technology.

Introduction and overview of the current situation regarding the employment of biomass

2014 ◽  
pp. 691-697
Author(s):  
Suleiman José Hassuani
Keyword(s):  
Sugar Industry ◽  
Energy Generation ◽  
Current Situation ◽  
The Other ◽  
Significant Excess ◽  
Cane Juice ◽  
Energy Needs ◽  
Long Time ◽  
Biomass Availability ◽  
Sugarcane Industry

The sugarcane industry for a long time has focused only on the cane juice, its extraction and conversion to sugar. Bagasse was considered a residue and burnt inefficiently to generate steam and power. In the last decades, bagasse gradually started to be converted into energy in a more efficient way, supplying all the sugar industry energy needs (power, and steam) and, in some cases, significant excess electricity has been exported to the grid, becoming another important source of revenue. This motivated several studies of more advanced energy generation systems to boost energy exports. In more recent years, technologies called 2nd and 3rd generation have taken over the scene with many options, promising to convert biomass into more valuable products such as biofuels, chemicals, fertilisers, pellets, etc. Unfilled expectations and opportunities are rising. On the other hand, these technologies are competing for the same biomass, and this has to be considered. The industry has started to question ‘which way to go’, strategy and investment wise. The present study provides a broad scenario for the biomass availability, and its employment, with a close view to the main processes and products that might have an important role in the future of the biomass in the sugarcane industry.

scholarly journals Does higher education properly prepare graduates for the growing artificial intelligence market? Gaps identification using text mining

2021 ◽  
pp. 1-13
Author(s):  
Lamiae Benhayoun ◽  
Daniel Lang
Keyword(s):  
Artificial Intelligence ◽  
Natural Language Processing ◽  
Text Mining ◽  
Natural Language ◽  
Language Processing ◽  
Academic Training ◽  
Market Requirements ◽  
Job Advertisements ◽  
The Individual

BACKGROUND: The renewed advent of Artificial Intelligence (AI) is inducing profound changes in the classic categories of technology professions and is creating the need for new specific skills. OBJECTIVE: Identify the gaps in terms of skills between academic training on AI in French engineering and Business Schools, and the requirements of the labour market. METHOD: Extraction of AI training contents from the schools’ websites and scraping of a job advertisements’ website. Then, analysis based on a text mining approach with a Python code for Natural Language Processing. RESULTS: Categorization of occupations related to AI. Characterization of three classes of skills for the AI market: Technical, Soft and Interdisciplinary. Skills’ gaps concern some professional certifications and the mastery of specific tools, research abilities, and awareness of ethical and regulatory dimensions of AI. CONCLUSIONS: A deep analysis using algorithms for Natural Language Processing. Results that provide a better understanding of the AI capability components at the individual and the organizational levels. A study that can help shape educational programs to respond to the AI market requirements.

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