The healthcare industry is changing at a fast rate. Recently, big data real time computing has been studied to enhance the quality of healthcare services and reduce costs making decisions in real-time. Artificial intelligence is used to track the big data. AI in healthcare sector could make treatment plans better, and also provide physicians information they need to make a good decision. This paper proposes a generic architecture for big data healthcare analytic by using open sources, including Apache Spark, Apache NiFi, Kafka, Tachyon, Gluster FS, Elastic search and NoSQL Cassandra. This paper will show the importance of applying AI based predictive and prescriptive analytics techniques in Health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real-time through an intelligent process analysis and big data processing.

AI Based HealthCare Platform for Real Time, Predictive and Prescriptive Analytics

Healthcare question answering (HQA) system plays a vital role in encouraging patients to inquire for professional consultation. However, there are some challenging factors in learning and representing the question corpus of HQA datasets, such as high dimensionality, sparseness, noise, nonprofessional expression, etc. To address these issues, we propose an inception convolutional autoencoder model for Chinese healthcare question clustering (ICAHC). First, we select a set of kernels with different sizes using convolutional autoencoder networks to explore both the diversity and quality in the clustering ensemble. Thus, these kernels encourage to capture diverse representations. Second, we design four ensemble operators to merge representations based on whether they are independent, and input them into the encoder using different skip connections. Third, it maps features from the encoder into a lower-dimensional space, followed by clustering. We conduct comparative experiments against other clustering algorithms on a Chinese healthcare dataset. Experimental results show the effectiveness of ICAHC in discovering better clustering solutions. The results can be used in the prediction of patients’ conditions and the development of an automatic HQA system.

An Inception Convolutional Autoencoder Model for Chinese Healthcare Question Clustering

Police Station is the most important unit for the citizens of the country (INDIA). Whenever a crime happens in the city a citizen first need to contact to the police station. Police stations in the city are still working manually such as filing an First Information Report (FIR) which are reported on paper due to this there are chances of miss placing those records. The Proposed online system- Intellectual and Enhance Digital Solutions (IEDS) for the Police Stations which will help the policeman and user to digitalize their work. This system will maintain the records in the database. IEDS integrate number of police stations in the city. Records like missing people, murder information, photo report, etc. helps the policeman to keep data in their pocket and search on single touch. IEDS also contains a user part for checking the status report which is accessed more securely by One-Time-Password (OTP). This System will also help lawyer to co-ordinate with policeman and victim by getting access to the documents uploaded by police. This System will also do Analysis of Criminal Records using Apriori Algorithm. The System will reduce the load of the policeman as well as local traffic in police station for queries like missing person, missing vehicle, status of their case etc. It will also reduce paper work which will in turn save trees.

Intellectual and Enhance Digital Solution For Police Station

The Internet has become a tool used to disseminate opinions in the form of product reviews, which significantly impact decisions to buy the product. Most previous studies have been done in this field using K-means algorithm, this study employs Python and Tableau to perform the sentiment analysis of the text as well as semantically classify the keywords into meaningful insights. Data were collected from Amazon website reviews ( $n=3,413$ ) of the product with the most reviews (Trigger Point Grid Foam Roller) in five different colors (black, camo, pink, orange, and lime) from 2018–2019. The results show that the black one has the most positive sentiment compared with the others. Moreover, SpaCy's named entity recognition revealed clusters of people, locations and purposes, or events, for the item. These results can help managers to develop the areas of a product where customers have expressed negative sentiments; moreover, this semantic classification results would help the manager to more effectively market the product.

Sentimental Visualization: Semantic Analysis of Online Product Reviews Using Python and Tableau

In India, there is a paper based medical record of all citizens dispersed at various dispensaries and hospitals. A lack of central repository does not provide complete information about any patient's medical history. These are some of the major setbacks in the fields of medical science. Our aim is to address some of these setbacks by using technology to aid medical science. This paper aims at providing a smart solution by developing a project that comprises of a repository for obtaining the entire medical records of any Indian citizen by linking their medical details to the Aadhar card. Currently, each and every Indian citizen's details have been linked to their Aadhar card which has become a unique identification of all Indian citizens. On the same lines, this project adopts the use of Aadhar card to provide unique identity to the medical records for deep analysis and management. In addition, using the concept of data mining, it provides various functionalities to doctors, who can analyze the medical records to improve their diagnosis & amalgamate their observations. Further, it comprises of a prediction system for predicting the diseases and disorders which use the concepts of machine learning and artificial neural networks & also provides online upload or download of medical reports. It also provides various functionalities to Indian citizens, who can get continuous notifications regarding dosage timings as prescribed by their doctors. Lastly, they can store their entire medical related information & view the dispensaries or hospitals based on the consultation charges and ratings. Additionally, it provides chemists with a functionality to analyze sales of a particular medicine in a particular area by using the concept of data mining to provide smart analysis.

Smart Analytics And Predictions For Indian Medicare

Taking care and maintenance of a healthy population is the Strategy of each country. Information and communication technologies in the health care system have led to many changes in order to improve the quality of health care services to patients, rational spending time and reduce costs. In the booming field of IT research, the reach of drug delivery, information on grouping of similar drugs has been lacking. The wealth distribution and drug affordability at a certain demographic has been interlinked and proposed in this paper. Looking at the demographic we analyze and group the drugs based on target action and link this to the wealth and the people to medicine ratio, which can be accomplished via data mining and web mining. The data thus mined will be analysed and made available to public and commercial purpose for their further knowledge and benefit.

Knowledge discovery, analysis and prediction in healthcare using data mining and analytics

Unleashing the Potential of Data Analytics Through Music

Microgrids, which make use of renewable resources, are a low-cost alternative to conventional methods of electricity generation for villages in India. Correctly identifying the suitable microgrid setup for an area according to the availability of local resources is extremely important to be able to get desired results and maximum profits. In order to make this process easier, we propose an algorithm which uses SAR images of the targeted area, captured over a period of time, to extract data about environmental factors of that area (solar heat, groundwater flow, erosion). This data is used to calculate the energy efficiency of each setup type and compare the economic viability of all, hence suggesting the best option. Thus, the system aims to ameliorate the decision-making process of microgrid setups in underdeveloped areas.

Mapping Urban Ecosystem Services Using Synthetic-Aperture Radar (SAR) Images from Satellite Data for Rural Microgrids in India

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Papers

Knowledge discovery, analysis and prediction in healthcare using data mining and analytics

Unleashing the Potential of Data Analytics Through Music

Mapping Urban Ecosystem Services Using Synthetic-Aperture Radar (SAR) Images from Satellite Data for Rural Microgrids in India