Role of Red Cell Indices in Screening for Beta Thalassemia Trait: an Assessment of the Individual Indices and Application of Machine Learning Algorithm

2020 ◽  
Author(s):  
Aarzoo Jahan ◽  
Garima Singh ◽  
Ruchika Gupta ◽  
Namrata Sarin ◽  
Sompal Singh
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Beta Thalassemia ◽  
Machine Learning Algorithm ◽  
Red Cell ◽  
Red Cell Indices ◽  
Thalassemia Trait ◽  
The Individual

scholarly journals Role of Naked Eye Single Tube Red Cell Osmotic Fragility Test (NESTROFT) in Detecting Beta-Thalassemia Trait

2018 ◽  
Vol 36 (4) ◽  
pp. 145-152 ◽  
Author(s):  
Asma Ferdousi ◽  
Mainuddin Ahmad ◽  
Jhulan Das Sharma ◽  
Rasheda Samad ◽  
AKM Zafar Ullah
Keyword(s):  
Predictive Value ◽  
Disease Incidence ◽  
Osmotic Fragility ◽  
Beta Thalassemia ◽  
Red Cell ◽  
College Hospital ◽  
Single Tube ◽  
Naked Eye ◽  
Thalassemia Trait

Thalassemia is one of the commonest inherited diseases in Bangladesh. The birth of a thalassemic child places considerable strain, not only on the affected child and its family but also on the community and the nation at large. To reduce the burden of the society and to reduce the disease incidence by providing genetic counseling, detection of carrier is important. The present study evaluates the role of ‘Naked Eye Single Tube Red Cell Osmotic Fragility Test’ (NESTROFT) in detecting ß-thalassemia trait. The current study is a cross sectional study done during the period of September 2008 to August 2009. The study subjects were sibs, parents and relatives of thalassemia patients of age more than 1 year attending Pediatric department of Chittagong Medical College Hospital. Sample size was 50. Here subjects with lowered osmotic fragility test were detected and later on Hb- electrophoresis was done. All the data were recorded and analyzed by SPSS programme. The Sensitivity, Specificity and predictive value of positive and negative tests were computed and they were 92.6%, 80%, 92.6% and 80% respectively. False positive cases were found. The present study found NESTROFT to be both sensitive and reasonably specific and of high negative predictive value. However, multicenter study with large sample is needed to recommend NESTROFT as a single screening test for detection of ß-thalassemia trait.J Bangladesh Coll Phys Surg 2018; 36(4): 145-152

scholarly journals Acute Diseases Prognosis using Chatbot

2021 ◽  
Vol 9 (VII) ◽  
Author(s):  
Shivanand Tiwari
Keyword(s):  
Machine Learning ◽  
Healthcare Professionals ◽  
Learning Algorithm ◽  
Early Stage ◽  
Machine Learning Algorithm ◽  
Patient Needs ◽  
Healthcare Organizations ◽  
Physician Time ◽  
Consultant Doctor

The role of chatbots in healthcare is to help free-up valuable physician-time by reducing or eliminating unnecessary doctor’s appointments. As the increase in cost, various healthcare organizations are looking for different ways to manage cost while improving the user’s experience. As we know there is shortage of healthcare professionals that makes it increasingly necessary for us to augment technology with health facilities in order to allow doctors to focus on more critical patient needs. Keeping this in Mind we are aiming to develop a Project that will basically ask for Symptoms from the Patient and perform the Prognosis on the basis of already developed dataset. The Machine Learning Algorithm will work on that dataset of symptoms and their prognosis to tell exactly what has happened to the Patient and will help to Reach the Desired Consultant/Doctor with respect to the Prognosis. It will also help the Patients to get Useful Information regarding different diseases that may help to deal with some Chronic Diseases at an early Stage!’

scholarly journals Energy-Centric Route Planning using Machine Learning Algorithm for Data Intensive Secure Multi-Sink Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 4866-4875
Keyword(s):  
Machine Learning ◽  
Sensor Network ◽  
Ad Hoc ◽  
Learning Algorithm ◽  
Route Planning ◽  
Security Requirements ◽  
Communication Link ◽  
Machine Learning Algorithm ◽  
Data Intensive ◽  
The Individual

Wireless sensor network (WSN) is energy operated self-disciplined ad-hoc technology capable of sensing and actuating environmental phenomenon. The sensed information is shared between communication sinks for access and processing. Energy conservation and route planning are prominent in determining the efficiency of the sensor network. In this paper, energy-centric route planning (ECRP) technique is introduced to address the inequalityin sensor node lifetime and routing along with security requirements. ECRP depends on the individual and co-operative energy expenses of the nodes to retain a balanced communication link. The expenses are monitored and a profitable route plan is designed using a machine learning algorithm that assists in identifying a non-deficient neighbor for routing. Both energy optimization and route refurbishing are controlled by the analysis and decisions of the learning algorithm. The Learning process is instigated with the node energy and current route neighbor information for discovering efficient communication paths to the sink. Security is administered using trust process in this path planning and routing for selecting reliable neighbors. This helps to retain security throughout the routing process.The impact of the proposed ECRP over sensor network is verified using the metrics: throughput, active nodes, transmitting energy, routing complexity and delay.

EVALUATION OF DIAGNOSTIC ACCURACY OF HEMATOLOGICAL INDICES IN THE DIFFERENTIATION OF BETA THALASSEMIA TRAIT FROM IRON DEFICIENCY ANEMIA

2021 ◽  
pp. 24-26
Author(s):  
Kavita Choudhary ◽  
M. L Gupta ◽  
Monika Hemin Shroff ◽  
Abhishek Rajawat
Keyword(s):  
Predictive Value ◽  
Hypochromic Anemia ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Red Cell ◽  
Hematological Indices ◽  
Medical College ◽  
Red Cell Indices ◽  
Thalassemia Trait ◽  
Youden’S Index

Background: 2 most frequent type of microcytic hypochromic anemias are Iron deciency anemia (IDA) and beta thalassemia trait (β-TT) continue to be a cause of signicant burden to the society, particularly in developing countries like INDIA, where there is limitation of resources. The objective of the present study was to evaluate the validity of different discrimination indices to differentiate β-TTfromIDA. Methods:All diagnosed patients of microcytic hypochromic anemia admitted in Geetanjali Medical College and Hospital, Udaipur (Raj) between Jan 2018 to June 2020, were included in this study. Sensitivity, specicity, positive predictive value (PPV), negative predictive value (NPV) and Youden's index (YI) were calculated. Result: According to our study following rankings of various discrimination indices were obtained for BTT patients, RDW Index > Mentzer's Index = Ehsani Index > Sirdah Index > MDHLIndex > MCHD Index. Conclusion: According to our results and observations, the percentage of correctly diagnosed patients are the highest with RDW Index and Mentzer's Index. It should be kept in mind that several studies have shown that none of the red cell indices carry 100% sensitivity and specicity in diagnosing BTT.

scholarly journals An analysis of NESTROFT and Red cell indices in evaluating antenatal mothers for Beta Thalassemia trait

2018 ◽  
Vol 17 (3) ◽  
pp. 411-416
Author(s):  
Rana Safia ◽  
Zeeba S Jairajpuri ◽  
Shaan Khetrapal ◽  
MJ Hassan ◽  
Monika Gupta ◽  
...  
Keyword(s):  
Health Care ◽  
Low Cost ◽  
Care Center ◽  
Medical Science ◽  
Osmotic Fragility ◽  
Beta Thalassemia ◽  
Red Cell ◽  
Health Care Center ◽  
Red Cell Indices ◽  
Thalassemia Trait

Background: The frequency of thalassemia trait is about 3% worldwide, while in developing countries like India, it is a major cause of burden on the health care system. Naked eye single tube red cell osmotic fragility test (NESTROFT) used in population screening for beta thalassemia trait. It is a simple, low cost, reliable and most suitable screening test for β BTT, with a sensitivity of 99.8% in regions with high prevalence rates.Material &Methods: The present study was conducted in the Department of Pathology and included a total of 174 antenatal cases, attending the Out Patient Department of Obstetrics and Gynecology of a tertiary health care center in New Delhi between June 2011 to January 2012. The aim of the study was to screen mothers antenatally for early detection of BTT and to test the validity of NESTROFT in detection of thalassemic carriers of this area.Results: 174 pregnant women attending antenatal clinics were screened for detecting hemoglobinopathy with the help of NESTROFT, red cell indices, haemoglobin electrophoresis and HPLC It was seen that only four cases were BTT while ten were of microcytic anaemia and two had normal red cell indices.Conclusion: antenatal diagnosis of BTT is an important screening programme to reduce the burden of birth of children suffering from thalassemia and other hemoglobinopathies.Bangladesh Journal of Medical Science Vol.17(3) 2018 p.411-416

Machine Learning Algorithm to Predict Early Complications after Brain Tumor Surgery

2018 ◽  
Author(s):  
C.H.B. van Niftrik ◽  
F. van der Wouden ◽  
V. Staartjes ◽  
J. Fierstra ◽  
M. Stienen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Tumor Surgery ◽  
Early Complications ◽  
Brain Tumor Surgery

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.

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