Abhishek Singh Rathore

• Ph.D
• Associate Professor at Shri Vaishnav Vidyapeeth Vishwavidyalaya

With the rapid growth of artificially intelligent algorithms, scientists have begun to utilize them in healthcare for decision support systems. The advancement and refinement of these algorithms improve the accuracy of these systems tremendously. The system is accurate but hides many aspects, like how it reaches the decision. The black box behavior...

Smart Agriculture is a revolutionary approach to farming that aims to increase crop yields, optimize resource usage, and reduce costs, through the use of technology the design and implementation of an AGRO-Cloud Model for crop yield prediction using hybrid deep learning. The proposed system aims to improve crop yield prediction accuracy and facilit...

This article proposes a cloud-based smart agriculture system for crop yield prediction using hybrid deep learning techniques. The study aims to improve crop yield prediction accuracy and facilitate decision-making for farmers. The system utilizes a hybrid deep learning approach that combines convolutional neural networks (CNNs) and recurrent neural...

An important factor influencing the global environment and public health scene is the Water Quality Index (WQI). Better water quality is correlated with a higher WQI, which benefits sustainable economic growth, environmental preservation, and public health. This emphasizes how crucial it is to preserve and improve water quality globally. The degree...

Crop disease detection is the process of identifying and classifying plant diseases from images or other data. This can be done manually or using automated methods. Manual methods typically involve a human expert visually inspecting the plant and identifying the disease. Automated methods use computer vision algorithms to identify the disease from...

Water is key to life on planet Earth, and hence, maintaining water quality is a critical issue in contemporary times. The water quality index decides the quality of drinking water. The presented work first explores different machine learning algorithms on the already collected water samples to decide the water quality and then applies the coalition...

In recent times, various machine learning approaches have been widely employed for effective diagnosis and prediction of diseases like cancer, thyroid, Covid-19, etc. Likewise, Alzheimer’s (AD) is also one progressive malady that destroys memory and cognitive function over time. Unfortunately, there are no dedicated AI-based solutions for diagnoses...

Erythemato-squamous diseases (ESD) diagnosis is a significant challenge in dermatology. It is divided into six categories. Artificial intelligence models have been applied to categorize these categories. Artificial intelligent models are black boxes in nature. The objective of this study is to unbox the black-box behavior and interpret the decision...

Healthcare and medicine are key areas where machine learning algorithms are widely used. The medical decision support systems thus created are accurate enough; however, they suffer from the lack of transparency in decision making and shows a black box behavior. However, transparency and trust are significant in the field of health and medicine, and...

Social media networks have grown rapidly as a key platform for communicating and sharing information. Millions of users are actively accessing its features and making connections. Normally, the only point of analyzing user authentication is for scrutinizing online details and posted information; however, this is sometimes morphed by cyber criminals...

In our competitive world, the lifestyles of human beings are very irregular. Irregularities in eating habits, daily routines, and workloads create a lot of tension that in turn leads to many chronic diseases. The four most prominent chronic diseases are heart disease, cancer, diabetes, and kidney disease. In this chapter, the potential of individua...

With digitization, a rapid growth is seen in educational technology. Different formal and informal learning contents are available on the internet. Intelligent tutoring system provides personalized e-learning to the learners. Different attributes like historical data, real-time data, behavioral, and cognitive are usually used for personalization. B...

In the modern era of information technology, machine learning algorithms are used in different domains for boosting the quality of decision making. The correct decision making about the disease diagnosis is one of the applications where these approaches are applied successfully for assisting the doctors. Correct and timely diagnosis of disease is t...

The regular use of online social networking has increased tremendously in recent time, and users present themselves in the form of posts and shares to the virtual world. This human specific-information is considered important and crucial and helps to understand the human behavior and in turns the personality of the person. Individual’s personality...

The Doubly Correlated Topic Model is a generative probabilistic topic model for automatically identifying topics from the corpus of the text documents. It is a mixed membership model, based on the fact that a document exhibits a number of topics. We used word co-occurrence statistical information for identifying an initial set of topics as posterio...

the research work presented here includes reengineering needs and process framework. It also includes various works that has been done in the field of extraction of business rules from legacy C++ source code. Therefore, here proposed method is implemented to extract a business rule from legacy C++ source code. Here we can extract information from l...