scholarly journals Using Handwriting Evaluation Software to Predict and Increase Diagnosis for Parkinson’s

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jordan King ◽  
Soo Park
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Paradigm Shift ◽  
Formal Evaluation ◽  
The World ◽  
Software Program ◽  
Diagnosis Method ◽  
Evaluation Programs ◽  
Learning Software ◽  
Similar Evaluation

Around the world, there currently exists a problem when it comes to the diagnosis of Parkinson’s disease (PD). Unfortunately, nearly half of all Americans who have PD remain undiagnosed, which is problematic when one considers the implications of such ignorance. People who continue to be undiagnosed do not have access to special treatments, therapies, and medications that would help alleviate the symptoms of PD and decrease the burden of it altogether. Fortunately, amidst recent technological advancements in computing and the contemporary paradigm shift to using handwriting as a diagnosis method for PD, a shimmer of hope reveals itself. By using a machine learning software program that predicts a user’s likelihood of having PD through their handwriting alone, people might feel more inclined to seek a formal evaluation for the disease. Since it is rather inexpensive, based on concrete, quantitative kinematics of an individual’s handwriting, and holds legitimacy due to the existence of similar evaluation programs, the software could help increase the amount of people that seek a formal PD evaluation and diagnosis.

scholarly journals A Gamified Assessment Platform for Predicting the Risk of Dementia +Parkinson’s disease (DPD) Co-Morbidity

2020 ◽  
Author(s):  
Zhiwei Zeng ◽  
Hongchao Jiang ◽  
Yanci Zhang ◽  
Zhiqi Shen ◽  
Jun Ji ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Detection ◽  
Predictive Analytics ◽  
Population Aging ◽  
Quality Care ◽  
Medical Conditions ◽  
Co Morbidity ◽  
The World

Population aging is becoming an increasingly important issue around the world. As people live longer, they also tend to suffer from more challenging medical conditions. Currently, there is a lack of a holistic technology-powered solution for providing quality care at affordable cost to patients suffering from co-morbidity. In this paper, we demonstrate a novel AI-powered solution to provide early detection of the onset of Dementia + Parkinson's disease (DPD) co-morbidity, a condition which severely limits a senior's ability to live actively and independently. We investigate useful in-game behaviour markers which can support machine learning-based predictive analytics on seniors' risk of developing DPD co-morbidity.

scholarly journals Conflict analysis for Turkish debates using text mining and text segmentation techniques

2017 ◽  
Vol 6 (2) ◽  
pp. 19-25
Author(s):  
Adem Karahoca ◽  
Dilek Karahoca ◽  
Efe Buyuk
Keyword(s):  
Machine Learning ◽  
Text Mining ◽  
Conflict Analysis ◽  
Text Segmentation ◽  
Correct Analysis ◽  
The World ◽  
Software Program ◽  
Turkish Language ◽  
Sentiment Word

Conflict Analysis is one of the most challenging issues in the world that many organizations and governments try to carry out perfectly. It is crucial to have a correct analysis to prepare a resolution for a problem. Thus, this study paper focuses on the ways that a software program can detect the reasons of arguments in a debate. The examples of debate dialogs are chosen from Turkish language because there is not much research in this area with this language. Moreover, the techniques which are applied in this work can also be applied to other languages, because a sentiment word dictionary is used and sentiments are almost the same in every language. This is a prepared dictionary from SentiWordNet with all the sentiment points for English words. It is translated and extended for the Turkish language. Furthermore, both machine learning and lexicon-based approaches are implemented in order to increase the diversity of results. This paper aims to show that languages can be processed in a technical manner and meanings can be extracted from sentences to understand the reasons of arguments. Likewise, the main contribution of this study is that conflict analysis for Turkish debates can be applied with the techniques which are examined here and they are also suitable for other languages.Conflict Analysis is one of the most challenging issues in the world that many organizations and governments try to carry out perfectly. It is crucial to have a correct analysis to prepare a resolution for a problem. Thus, this study paper focuses on the ways that a software program can detect the reasons of arguments in a debate. The examples of debate dialogs are chosen from Turkish language because there is not much research in this area with this language. Moreover, the techniques which are applied in this work can also be applied to other languages, because a sentiment word dictionary is used and sentiments are almost the same in every language. This is a prepared dictionary from SentiWordNet with all the sentiment points for English words. It is translated and extended for the Turkish language. Furthermore, both machine learning and lexicon-based approaches are implemented in order to increase the diversity of results. This paper aims to show that languages can be processed in a technical manner and meanings can be extracted from sentences to understand the reasons of arguments. Likewise, the main contribution of this study is that conflict analysis for Turkish debates can be applied with the techniques which are examined here and they are also suitable for other languages.

Feature extraction and prediction of Dengue Outbreaks

2020 ◽  
pp. 216-222
Author(s):  
Kunal Parikh ◽  
Tanvi Makadia ◽  
Harshil Patel
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Developing Countries ◽  
Feature Extraction ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Health Concerns ◽  
The World ◽  
Dengue Outbreaks

Dengue is unquestionably one of the biggest health concerns in India and for many other developing countries. Unfortunately, many people have lost their lives because of it. Every year, approximately 390 million dengue infections occur around the world among which 500,000 people are seriously infected and 25,000 people have died annually. Many factors could cause dengue such as temperature, humidity, precipitation, inadequate public health, and many others. In this paper, we are proposing a method to perform predictive analytics on dengue’s dataset using KNN: a machine-learning algorithm. This analysis would help in the prediction of future cases and we could save the lives of many.

Platform for Analysing and Encouraging Student Activity on Contest and E-learning Systems

2018 ◽  
Vol 12 ◽  
pp. 85-98
Author(s):  
Bojan Kostadinov ◽  
Mile Jovanov ◽  
Emil STANKOV
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Educational Policy ◽  
Learning Systems ◽  
Data Sources ◽  
Or Education ◽  
Student Activity ◽  
The World ◽  
E Learning ◽  
Analyse Data

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.

Multiclass machine learning classification of functional brain images for Parkinson's disease stage prediction

2020 ◽  
Vol 13 (5) ◽  
pp. 508-523 ◽  
Author(s):  
Guan‐Hua Huang ◽  
Chih‐Hsuan Lin ◽  
Yu‐Ren Cai ◽  
Tai‐Been Chen ◽  
Shih‐Yen Hsu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Stage ◽  
Brain Images ◽  
Functional Brain ◽  
Machine Learning Classification

scholarly journals Current Understanding of Novel Coronavirus: Molecular Pathogenesis, Diagnosis, and Treatment Approaches

Immuno ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 30-66
Author(s):  
Niraj Kumar Jha ◽  
Madhan Jeyaraman ◽  
Mahesh Rachamalla ◽  
Shreesh Ojha ◽  
Kamal Dua ◽  
...  
Keyword(s):  
Paradigm Shift ◽  
Functional Outcomes ◽  
Cellular Therapy ◽  
Treatment Modalities ◽  
Unknown Etiology ◽  
Huge Number ◽  
The World ◽  
To Come ◽  
Novel Coronavirus ◽  
Nano Medicine

An outbreak of “Pneumonia of Unknown Etiology” occurred in Wuhan, China, in late December 2019. Later, the agent factor was identified and coined as SARS-CoV-2, and the disease was named coronavirus disease 2019 (COVID-19). In a shorter period, this newly emergent infection brought the world to a standstill. On 11 March 2020, the WHO declared COVID-19 as a pandemic. Researchers across the globe have joined their hands to investigate SARS-CoV-2 in terms of pathogenicity, transmissibility, and deduce therapeutics to subjugate this infection. The researchers and scholars practicing different arts of medicine are on an extensive quest to come up with safer ways to curb the pathological implications of this viral infection. A huge number of clinical trials are underway from the branch of allopathy and naturopathy. Besides, a paradigm shift on cellular therapy and nano-medicine protocols has to be optimized for better clinical and functional outcomes of COVID-19-affected individuals. This article unveils a comprehensive review of the pathogenesis mode of spread, and various treatment modalities to combat COVID-19 disease.

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