Early Diagnosis Of People Research Articles

Coronavirus diagnosis using cough sounds: Artificial intelligence approaches.

The Coronavirus disease 2019 (COVID-19) pandemic has caused irreparable damage to the world. In order to prevent the spread of pathogenicity, it is necessary to identify infected people for quarantine and treatment. The use of artificial intelligence and data mining approaches can lead to prevention and reduction of treatment costs. The purpose of this study is to create data mining models in order to diagnose people with the disease of COVID-19 through the sound of coughing. In this research, Supervised Learning classification algorithms have been used, which include Support Vector Machine (SVM), random forest, and Artificial Neural Networks, that based on the standard "Fully Connected" neural network, Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) recurrent neural networks have been established. The data used in this research was from the online site sorfeh.com/sendcough/en, which has data collected during the spread of COVID-19. With the data we have collected (about 40,000 people) in different networks, we have reached acceptable accuracies. These findings show the reliability of this method for using and developing a tool as a screening and early diagnosis of people with COVID-19. This method can also be used with simple artificial intelligence networks so that acceptable results can be expected. Based on the findings, the average accuracy was 83% and the best model was 95%.

Adapted MMSE and TYM cognitive tests: how much powerful in screening for Alzheimer’s disease in Iranian people

Alzheimer’s disease (AD) is a major global health priority and providing an efficient way for early diagnosis of people developing dementia is important. The Mini-Mental State Examination (MMSE, total score = 30) and Test Your Memory (TYM, total score = 50) are widely used as screening tests for cognitive function. In the present study 174 subjects including healthy people (CON group) and those having Alzheimer’s disease (AD group) were introduced to MMSE and TYM cognitive tests adjusted to Iranian population. Sensitivities and specificities with optimal cut-off scores, area under curve (AUC), positive predictive value (PPV) and negative predictive value (NPV) were measured for both tests. The MMSE scores of the CON and AD groups were 23.77 ± 0.327 and 10.88 ± 0.762, respectively. The TYM scores were 44.32 ± 0.389 and 14.37 ± 1.368 in the CON and AD participants, respectively. Findings in the MMSE test were: AUC = 0.962, optimal cut-off score = 18.5, sensitivity = 0.90 and specificity = 0.96. Values in the TYM test were: AUC = 0.991, optimal cut-off score = 31, sensitivity = 0.90 and specificity = 1. We found no correlation between the cognitive performance and age in the CON group but a positive correlation in the AD patients. On the other hand, t-test analysis indicated that achievement of the test scores are significantly sex dependent, with more scores attained by the females. Taken together, in regard to correct classification rate (CCR); the TYM test seems to be more appropriate for cognitive screening in our study. However, considering an analogous AUC, both tests are comparable and have high sensitivity and specificity for discriminating between people with and without AD.

Nucleic acid amplification techniques (NAATs) for early diagnosis of HIV-1 and HIV-2 infections

This is the protocol for a review and there is no abstract. The objectives are as follows: Our primary objective is to assess the diagnostic accuracy (sensitivity and specificity) of NAATs (both quantitative and qualitative) for early diagnosis of people of all ages with suspected HIV-1 and -2 infections. We hypothesize that their accuracy for early diagnosis will be as good as the diagnosis at a later stage. We furthermore hypothesize that there will be no differences in diagnostic accuracy between the different molecular tests when evaluated against the same reference standard. We defined early detection as a period that is consistently between one and three weeks (Busch 1997; Fiebig 2003). The secondary objective of this review is to assess the influence of sources of heterogeneity on the diagnostic accuracy of tests performed, in particular the type of HIV (HIV-1 or HIV-2), different cut-off values, different samples, the healthcare setting, age of the participants, differences in timing of the tests, to investigate how the time of testing relates to accuracy; and study design features.

OP0245-PARE Easier Access to Rheumatologist and Early Diagnose

BackgroundIt is well known that diagnose of most of the rheumatic diseases sometimes take several months or couple of years and more. Reasons for that could be quite different –...

On-Shoe Wearable Sensors for Gait and Turning Assessment of Patients With Parkinson's Disease

Assessment of locomotion through simple tests such as timed up and go (TUG) or walking trials can provide valuable information for the evaluation of treatment and the early diagnosis of people with Parkinson's disease (PD). Common methods used in clinics are either based on complex motion laboratory settings or simple timing outcomes using stop watches. The goal of this paper is to present an innovative technology based on wearable sensors on-shoe and processing algorithm, which provides outcome measures characterizing PD motor symptoms during TUG and gait tests. Our results on ten PD patients and ten age-matched elderly subjects indicate an accuracy ± precision of 2.8 ± 2.4cm/s and 1.3 ± 3.0cm for stride velocity and stride length estimation compared to optical motion capture, with the advantage of being practical to use in home or clinics without any discomfort for the subject. In addition, the use of novel spatio-temporal parameters, including turning, swing width, path length, and their intercycle variability, was also validated and showed interesting tendencies for discriminating patients in ON and OFF states and control subjects.

Empowerment and decision-making for people with dementia: The use of legal interventions in Scotland

Dementia is associated with a decline in the ability to reason and make judgements thereby affecting a person's ability to make sound decisions. Others are not legally entitled to make these decisions until they have been assigned legal jurisdiction to do so. It is not clear, however, the extent to which people with dementia rely on available legal interventions. The growing emphasis on early diagnosis for people with dementia provides an opportunity for people to plan and control decisions about financial management and welfare and may well lead to an increase in the uptake of these interventions. This paper coincides with a move to reform outdated Scottish Law with the Adults with Incapacity (Scotland) Act 2000. This legislation proposes a more integrated and flexible approach to the legal management of the affairs of people with reduced decision-making capability. The paper reviews of the recent literature on the use of legal interventions for people with dementia and their families, and discusses the empowering or disempowering nature of the interventions.

Caring for older people with dementia

Margaret M Brown investigates how practice nurses can contribute to the early diagnosis of people with dementia in light of the National Service Framework for Older People. She shows that opportunities exist to work in conjunction with other health and social services for the ongoing care of these people.