Volume 10 | Issue 11 |

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Parable, Allegory, Nuclear Explosion, Brahmastra, Chronicle, Peacocks.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Aalochako ki drushti me kamayani ke stree patra-ek samshya

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Aalochako ki drushti me kamayani ke stree patra-ek samshya

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nowadays there is a lot of imbalanced data present on the web in several areas like medical, business, insurance, banks, research centers, and so on. All these imbalanced data are creating a lot of gaps for the researchers to gain any new information based on the primitive data. Since the corona virus emerged, it has been increasingly difficult to get legitimate therapeutic resources, such as the scarcity of specialists and healthcare professionals, appropriate equipment and medications, etc. There are many deaths as a result of the medical profession as a whole being in distress. People started taking medications independently without the proper consultation because they weren't readily available, which made their health conditions worse than usual. Recently, machine learning has proven useful in a variety of applications, and creative work for automation is on the rise. The goal of this research is to present a medicine recommendation system that significantly decreases the need for specialists. Because they are doctor-friendly, emerging technologies like machine learning, deep learning, and data mining can help us investigate the history of medicine and lower medical errors. In order to identify the top few medications for a condition, this research suggests a drug recommendation system that uses word2vec sentiment analysis on patient review data

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Drug Recommendation System on Imbalanced Medical Data Using SMOTE

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background:Lesser number of undergraduate (UG) MBBS students carries the concept of biomedical research. In order to achieve the endeavour of creating globally at par Indian medical graduates, it appears obligatory to introduce research aptitude among UG medical students. More than a decade back, Medical Education Unit of SBKS Medical Institute& Research Centre, SumandeepVidyapeeth, formulated and running a research orientation programme to involve and enrich the UG medical students in biomedical research during their 3rd first professionals . The programme is named as Evidence Generating Community Health Intervention Project(EviGenCHIP). Aims and Objectives:1. To evaluate the impact of EviGenCHIP Programme. 2. To assess research aptitude and research profile of the trained students.3.To appraise feedback from the faculty about the programme. Methodology: This was an observational study conducted at department of Forensic Medicine & Toxicology, SBKSMI&RC in duration of 4 months after approval from Institutional Ethics Committee. A Quantitative & Qualitative study conducted on UG students and teaching faculties trained under EviGenCHIP. Total number of students participated in this study were 100 for quantitative study. 4 batches of focused group, each group comprising of 6 students, i.e. 24 students and one group of 6 faculties were be recruited for qualitative study. Non-randomised sampling method was adopted to recruit the participants in Focused Group Discussion. Observations: This programme does have an impact on most of the students who participated in this programme which is reflected in content analysis of Focus group discussion and Quantitative data analysis. Conclusion: This unique programme is a necessity in formal medical undergraduate education and those students who were interested and are properly mentored reflected positive impact on their research aptitude.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Community research, UG Medical teaching, Focused Group Discussion, Impact evaluation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Obese individuals have a high possibility of developing Cardio Vascular Disease (CVD), which should be because of an alteration in the Autonomic Nervous System (ANS) .Heart Rate Variability (HRV) can be utilized to recognize the progressions in ANS movement. An HRV is a device to gauge the ANS action utilizing linear and non- linear HRV features. In this paper, we address the impact of weight on ANS utilizing HRV parameters. At first, two sets of twenty counts are taken; one set contains obesity and one more set is non-obesity regardless of gender, between the ages of 20 to 50. The measurably massive distinction between the two sets was noticed using the Independent t-test. Measurable consequences of the review show the sympathovagal imbalance because of reduced parasympathetic movement. To come up with exact outcomes, we executed deep learning techniques. This paper essentially represents two best profound learning calculations: RNN (Recurrent Neural Network) and LSTM (Long Short-Term Memory). The experimental results show that the LSTM expectation impact is superior to RNN in terms of recognizing CVD.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deep learning, RNN, LSTM, CVD, ANS.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The purpose of Artificial intelligence (AI) in marketing is to continually monitor and anticipate the next purchase decision of the consumers in mind and improve their overall "journey." The potential of AI can be seen in its primary components: big data, machine learning, and robust solutions. The idea"big data "big data" means that marketers can combine and categorize massive quantities of data using a minimum of manual effort. Utilizing this data, they can be confident that they will send the correct message to the appropriate people at the right moment through the preferred channel. Machine learning (deep learning) lets marketers comprehend and draw logic from huge data collection. They can predict consumption trends, track and analyze customer purchases, and predict future customer behavior. Producing robust solutions means that we are in a time when machines can comprehend the world the same as we do. Devices can recognize concepts and themes in the spectrum of data, interpret emotions and human communication, and provide appropriate responses to the needs of consumers. They can quickly determine the behavior and choices of buyers and then use the data to address issues in the future. In the years to come, marketers can expect more significant AI impact through better-informed searches, more effective ads, improved content delivery, reliance on bots, and continuous learning. They protect against fraudulent activities and data breaches such as sentiment analysis, image and voice recognition, sales forecasts, and language recognition, as well as predictors of customer services, segmentation of customers, and more. This paper seeks to determine the relationship between marketers and AI machines.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial intelligence, marketing, machine learning, powerful solutions, bots, marketers, big data

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The goal of this research was to make an assessment of where AI and ML have been applied so far in agriculture and to make some educated speculations about where the field might go from here. This research takes a systematic literature review approach to the articles already published across a variety of scientific platforms that explore the overlap between artificial intelligence (AI) and supply chain management (SC) and machine learning (ML) in the food industry (FT). In this work, we propose a strategy for decreasing agricultural risks and bolstering smart farming practises. The wireless AI-based sensor will raise the bar for intelligent agriculture, which has seen progress in the past. In order to improve prediction in its current form, this research uses image-processing based machine learning techniques. Detecting and controlling cotton leaf diseases is the main objective of this study. The study covers a wide range of topics, including the detection of diseases on leaves, a server-based remote monitoring system, moisture and temperature sensing, and soil sensing. Plant illnesses caused by insects and other pathogens can drastically cut harvest yields if not treated promptly. In this study, we describe a system for assessing soil quality and warding against diseases that affect cotton leaves. Artificial intelligence's regression technique is used by the proposed system to detect and categorise leaf rots. After the virus

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

STUDY AND ANALYSIS ON MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE FOR SMART AGRICULTURE

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

According to modern science Karshya can be correlated with under nutrition. According to WHO adolescent constitute 20% of global population and near about 22% of Indian population Nutritional deficiency and iron deficiency anemia are very common and has a negative effect on their growth and development. In modern era false habit of taking food without the urge of hunger, fast food, junk food growing rapidly in Indian culture. Late night sleep is the major reason to worsen mental and social health of young generation. These faulty habit leads to Mandagni which directly affects digestion. According to Sushruta due to the diet and various procedures including both physical and mental which pacifies Vata Dosha causes improper formation of Rasadhatu (either in less amount or with default) causing improper formation of succeeding Dhatu resulting in Karshya. So role of Abhyanga and diet modification plays important role in the management of Karshya. Ayurveda has its uniqueness in the prevention of any disease. For it in the classics daily regimen has been mentioned (Dinacharya Upakrama). Abhyanga (Ayurvedic oil massage) described in the ancient science and practicized all over the globe in various form has both preventive and curative effect and found beneficial in many diseases. So the topic taken to study the efficacy of Ashwagandha Tail Abhyanga in the management of Karshya.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

- karshya,abhyang ,ashwagandha tail

  License

Creative Commons Attribution 4.0 and The Open Definition