Mouse-Less Cursor Control for Quadriplegic and Autistic Patients Using Artificial Intelligence

2021 ◽  
pp. 105-137
Author(s):  
Aman Sharma ◽  
Saksham Chaturvedi
Keyword(s):  
Artificial Intelligence ◽  
Human Intelligence ◽  
Cursor Control ◽  
Detection Analysis ◽  
Autistic People ◽  
Social Abilities ◽  
Motor Difficulties ◽  
Detection And Diagnosis ◽  
Technology Aids ◽  
Early Detection And Diagnosis

Artificial intelligence is a field within computer science that attempts to simulate and build enhanced human intelligence into computers, mobiles, and various other machines. It can be termed as a powerful tool that has the capability to process huge sums of information with ease and assess patterns created over a period of time to give significant results or suggestions. It has garnered focus from almost every field from education to healthcare. Broadly, AI applications in healthcare include early detection and diagnosis, suggesting treatments, evaluating progress, medical history, and predicting outcomes. This chapter discussed AI, ASD, and what role AI currently plays in advancing autistic lives including detection, analysis, and treatment of ASD and how AI has been improving healthcare and the existing medical and technology aids available for autistic people. Current and future advancements are discussed and suggested in the direction of improving social abilities and reducing the communication and motor difficulties faced by people with ASD.

scholarly journals AN IN-DEPTH ANALYSIS OF THE IDENTIFIED ALGORITHMS AND THEIR COMPARATIVE STUDY IN THE EARLY DETECTION AND DIAGNOSIS OF BREAST CANCER

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mridul Sharma
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Early Detection ◽  
Healthcare Workers ◽  
State Of The Art ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Depth Analysis ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

These days one of the major inevitable ailments for females is bosom malignancy. The appropriate medication and early findings are important stages to take to thwart this ailment. Although, it's not easy to recognize due to its few vulnerabilities and lack of data. Can use artificial intelligence to create devices that can help doctors and healthcare workers to early detection of this cancer. In This research, we investigate three specific machine learning algorithms widely used to detect bosom ailments in the breast region. These algorithms are Support vector machine (SVM), Bayesian Networks (BN) and Random Forest (RF). The output in this research is based on the State-of-the-art technique.

scholarly journals A Review of Diabetes Mellitus Detection using Machine Learning Techniques

2021 ◽  
Vol 10 (6) ◽  
pp. 32-41
Author(s):  
R Kumar ◽  
Pazhanirajan S
Keyword(s):  
Artificial Intelligence ◽  
Diabetes Mellitus ◽  
Machine Learning ◽  
Machine Learning Techniques ◽  
Self Management ◽  
Self Administration ◽  
Comprehensive Overview ◽  
Learning Techniques ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

Diabetes Mellitus (DM) is a disease that can lead to a multi-organ malfunctioning in patients due to non-regulated diabetes. Recent advancements in machine learning (ML) and artificial intelligence, the early detection and diagnosis of DM is more advantageous than the manual diagnosis through an automated process. It this review, DM's recognition, diagnosis and self-management techniques from six facets, namely DM datasets, techniques involved in pre-processing, extraction of features; identification through ML; classification and diagnosis of DM; intelligent DM assistant based on artificial intelligence; are thoroughly analyzed and presented. The findings of the previous research and their inferences are interpreted. This analysis also offers a comprehensive overview of DM detection and self-administration technologies that can be of use to the research community working in the field of automated DM detection and self-management.

scholarly journals Early-Stage Detection of Cancer in Breast Using Artificial Intelligence

2021 ◽  
Vol 11 (2) ◽  
pp. 2016-2028
Author(s):  
M.N. Vimal Kumar ◽  
S. Aakash Ram ◽  
C. Shobana Nageswari ◽  
C. Raveena ◽  
S. Rajan
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Deep Learning ◽  
Learning Algorithm ◽  
Early Stage ◽  
Deep Learning Algorithm ◽  
Common Cancer ◽  
Abnormal Cells ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

One of the deadly diseases among humans is Cancer, which occurs almost anywhere in the human body. Cancer is caused by the cells that spread into the surrounding tissues by dividing itself uncontrollably. Breast Cancer is the most common cancer among women. Early detection and diagnosis of breast cancer are treatable and curable. Many women have no symptoms for this cancer at an early stage. The abnormal cells in the breast will risk for the development of breast cancer. So, it is important for women to regularly examine their breast. Technologies can be utilized in a smarter way with Artificial Intelligence techniques to assist the women during their examination of the breast at their living place to avoid the risk of breast cancer. The main aim is to develop a lowcost self-examining device for the detection of breast cancer and abnormality in the breast using an efficient optical method, Deep-learning algorithm and Internet of Things.

Artificial Intelligence in Healthcare

2021 ◽  
Vol 9 (VIII) ◽  
pp. 309-311
Author(s):  
Shrey Bhagat
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Medical Specialties ◽  
Current State ◽  
Wide Range ◽  
Care Information ◽  
Structured Knowledge ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

Artificial intelligence aspires to imitate the psychological functions of humans. It ushers in a perfect change in care, fueled by the rising accessibility of care information and the rapid advancement of analytics approaches. We prefer to assess the current state of AI applications in healthcare and speculate on their future. AI is being used to apply a wide range of care expertise. Machine learning algorithms for structured knowledge, such as the traditional support vector machine and neural network, and therefore the popular deep learning, as well as the tongue process for unstructured knowledge, are typical AI approaches. Cancer, neurology, medical specialties, and strokes are all major disease areas that employ AI technologies. We therefore go over AI applications in stroke in more depth, focusing on the three key areas of early detection and diagnosis, as well as outcome prediction and prognosis analysis.

scholarly journals Artificial Intelligence in Predicting Heart Failure

2021 ◽  
Author(s):  
Rashid Ebrahim Al-Mannai ◽  
Mohammed Hamad Almerekhi ◽  
Mohammed Abdulla Al-Mannai ◽  
Mishahira N ◽  
Kishor Kumar Sadasivuni ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Heart Failure ◽  
Health Care Systems ◽  
Critical Role ◽  
Failure Detection ◽  
Major Chronic Disease ◽  
Care Systems ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

Heart Failure is a major chronic disease that is increasing day by day and a great health burden in health care systems world wide. Artificial intelligence (AI) techniques such as machine learning (ML), deep learning (DL), and cognitive computer can play a critical role in the early detection and diagnosis of Heart Failure Detection, as well as outcome prediction and prognosis evaluation. The availability of large datasets from difference sources can be leveraged to build machine learning models that can empower clinicians by providing early warnings and insightful information on the underlying conditions of the patients

Detection of Leukemia Using Image Processing

2018 ◽  
Vol 8 (4) ◽  
pp. 61
Author(s):  
A. Sivasangari ◽  
G. Sasikumar
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Early Detection ◽  
Visual Inspection ◽  
Causes Of Death ◽  
Cure Rate ◽  
Blood Disorders ◽  
Detection And Diagnosis ◽  
The Moment ◽  
Early Detection And Diagnosis

Leukemia   disease   is one   of    the   leading   causes   of death   among   human. Its  cure  rate and  prognosis   depends   mainly   on  the  early  detection   and  diagnosis  of   the  disease. At  the  moment, identification  of  blood  disorders  is  through   visual  inspection  of  microscopic  images  by  examining  changes  like  texture, geometry, colour  and   statistical  analysis  of  images . This  project  aims  to  preliminary  of  developing  a  detection  of  leukemia  types  using   microscopic  blood  sample using MATLAB. Images  are  used  as  they  are  cheap  and  do  not  expensive  for testing  and  lab  equipment.

Intelligence, Artificial and Otherwise

2019 ◽  
Vol 24 (2) ◽  
pp. 241-258
Author(s):  
Paul Dumouchel
Keyword(s):  
Artificial Intelligence ◽  
Human Intelligence

The idea of artificial intelligence implies the existence of a form of intelligence that is “natural,” or at least not artificial. The problem is that intelligence, whether “natural” or “artificial,” is not well defined: it is hard to say what, exactly, is or constitutes intelligence. This difficulty makes it impossible to measure human intelligence against artificial intelligence on a unique scale. It does not, however, prevent us from comparing them; rather, it changes the sense and meaning of such comparisons. Comparing artificial intelligence with human intelligence could allow us to understand both forms better. This paper thus aims to compare and distinguish these two forms of intelligence, focusing on three issues: forms of embodiment, autonomy and judgment. Doing so, I argue, should enable us to have a better view of the promises and limitations of present-day artificial intelligence, along with its benefits and dangers and the place we should make for it in our culture and society.

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