scholarly journals Ethical Implications of Alzheimer’s Disease Prediction in Asymptomatic Individuals Through Artificial Intelligence

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 440
Author(s):  
Frank Ursin ◽  
Cristian Timmermann ◽  
Florian Steger
Keyword(s):  
Artificial Intelligence ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Adequate Treatment ◽  
Ethical Implications ◽  
Predictive Tests ◽  
Positive Balance ◽  
Asymptomatic Individuals ◽  
The Right

Biomarker-based predictive tests for subjectively asymptomatic Alzheimer’s disease (AD) are utilized in research today. Novel applications of artificial intelligence (AI) promise to predict the onset of AD several years in advance without determining biomarker thresholds. Until now, little attention has been paid to the new ethical challenges that AI brings to the early diagnosis in asymptomatic individuals, beyond contributing to research purposes, when we still lack adequate treatment. The aim of this paper is to explore the ethical arguments put forward for AI aided AD prediction in subjectively asymptomatic individuals and their ethical implications. The ethical assessment is based on a systematic literature search. Thematic analysis was conducted inductively of 18 included publications. The ethical framework includes the principles of autonomy, beneficence, non-maleficence, and justice. Reasons for offering predictive tests to asymptomatic individuals are the right to know, a positive balance of the risk-benefit assessment, and the opportunity for future planning. Reasons against are the lack of disease modifying treatment, the accuracy and explicability of AI aided prediction, the right not to know, and threats to social rights. We conclude that there are serious ethical concerns in offering early diagnosis to asymptomatic individuals and the issues raised by the application of AI add to the already known issues. Nevertheless, pre-symptomatic testing should only be offered on request to avoid inflicted harm. We recommend developing training for physicians in communicating AI aided prediction.

scholarly journals Novel Trends in Electrochemical Biosensors for Early Diagnosis of Alzheimer’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Pavla Valkova ◽  
Miroslav Pohanka
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Neurodegenerative Disorder ◽  
Electrochemical Biosensors ◽  
Standard Laboratory ◽  
Blood Samples ◽  
Number Of Patients ◽  
Asymptomatic Phase ◽  
The Right

Background. Alzheimer’s disease (AD) is a multifactorial progressive and irreversible neurodegenerative disorder affecting mainly the population over 65 years of age. It is becoming a global health and socioeconomic problem, and the current number of patients reaching 30–50 million people will be three times higher over the next thirty years. Objective. Late diagnosis caused by decades of the asymptomatic phase and invasive and cost-demanding diagnosis are problems that make the whole situation worse. Electrochemical biosensors could be the right tool for less invasive and inexpensive early diagnosis helping to reduce spend sources— both money and time. Method. This review is a survey of the latest advances in the design of electrochemical biosensors for the early diagnosis of Alzheimer’s disease. Biosensors are divided according to target biomarkers. Conclusion. Standard laboratory methodology could be improved by analyzing a combination of currently estimated markers along with neurotransmitters and genetic markers from blood samples, which make the test for AD diagnosis available to the wide public.

scholarly journals Position Statement on Anti-Dementia Medication for Alzheimer’s Disease by Swiss Stakeholders

2021 ◽  
Vol 5 (2) ◽  
pp. 14
Author(s):  
Giovanni Frisoni ◽  
Jean-Marie Annoni ◽  
Stefanie Becker ◽  
Tim Brockmann ◽  
Markus Buerge ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Health Care ◽  
Early Diagnosis ◽  
Old Age ◽  
State Of The Art ◽  
Position Statement ◽  
Swiss Health ◽  
The Right ◽  
To Receive

The present document represents the position of Swiss health-care associations, clinical and research centers, research-supporting foundations, and the association Alzheimer Switzerland regarding the care of persons with dementia and Alzheimer’s disease. We claim that dementia is not part of normal aging but a disease developing more frequently in old age; early diagnosis and treatment of dementia is paramount; all patients with dementia have the right to receive state-of-the-art treatments; more intense information, education, and counseling on dementia are necessary; media should provide balanced and fair reporting of scientific discoveries on Alzheimer’s and dementia; all patients with dementia have the right to be treated; anti-dementia drugs should be used and accompanied by listening, compassion, and understanding.

An insight into the role of Artificial Intelligence in the early diagnosis of Alzheimer’s disease

2021 ◽  
Vol 20 ◽  
Author(s):  
Rohit Kumar Verma ◽  
Manisha Pandey ◽  
Pooja Chawla ◽  
Hira Choudhury ◽  
Jayashree Mayuren ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Symptomatic Relief ◽  
Large Data ◽  
Successful Implementation ◽  
Clinical Implementation ◽  
Insight Into

Background: The complication of Alzheimer’s disease (AD) has made the development of its therapeutic a challenging task. Even after decades of research, we have achieved no more than a few years of symptomatic relief. The inability to diagnose the disease early is the foremost hurdle behind its treatment. Several studies have aimed to identify potential biomarkers that can be detected in body fluids (CSF, blood, urine, etc) or assessed by neuroimaging (i.e., PET and MRI). However, the clinical implementation of these biomarkers is incomplete as they cannot be validated. Method: To overcome the limitation, the use of artificial intelligence along with technical tools has been extensively investigated for AD diagnosis. For developing a promising artificial intelligence strategy that can diagnose AD early, it is critical to supervise neuropsychological outcomes and imaging-based readouts with a proper clinical review. Conclusion: Profound knowledge, a large data pool, and detailed investigations are required for the successful implementation of this tool. This review will enlighten various aspects of early diagnosis of AD using artificial intelligence.

scholarly journals The PredictAD project: development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease

2013 ◽  
Vol 3 (2) ◽  
pp. 20120072 ◽  
Author(s):  
Kari Antila ◽  
Jyrki Lötjönen ◽  
Lennart Thurfjell ◽  
Jarmo Laine ◽  
Marcello Massimini ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Developed Countries ◽  
New Drugs ◽  
Brain Images ◽  
Age Related ◽  
Number Of Patients ◽  
Irreversible Effects ◽  
The Right

Alzheimer's disease (AD) is the most common cause of dementia affecting 36 million people worldwide. As the demographic transition in the developed countries progresses towards older population, the worsening ratio of workers per retirees and the growing number of patients with age-related illnesses such as AD will challenge the current healthcare systems and national economies. For these reasons AD has been identified as a health priority, and various methods for diagnosis and many candidates for therapies are under intense research. Even though there is currently no cure for AD, its effects can be managed. Today the significance of early and precise diagnosis of AD is emphasized in order to minimize its irreversible effects on the nervous system. When new drugs and therapies enter the market it is also vital to effectively identify the right candidates to benefit from these. The main objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data, electrophysiological measurements of the brain and structural, functional and molecular brain images. We also designed and built a statistical model and a framework for exploiting these biomarkers with other available patient history and background data. We were able to discover several potential novel biomarker candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials.

A Transfer Learning Approach for Early Diagnosis of Alzheimer’s Disease on MRI Images

Neuroscience ◽  
2021 ◽  
Author(s):  
Atif Mehmood ◽  
Shuyuan yang ◽  
Zhixi feng ◽  
Min wang ◽  
AL Smadi Ahmad ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Transfer Learning ◽  
Learning Approach

scholarly journals The Role of Salivary Biomarkers in the Early Diagnosis of Alzheimer’s Disease and Parkinson’s Disease

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 371
Author(s):  
Patrycja Pawlik ◽  
Katarzyna Błochowiak
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Neurodegenerative Diseases ◽  
Diagnostic Tool ◽  
Clinical Symptoms ◽  
Early Screening ◽  
Salivary Biomarkers

Many neurodegenerative diseases present with progressive neuronal degeneration, which can lead to cognitive and motor impairment. Early screening and diagnosis of neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) are necessary to begin treatment before the onset of clinical symptoms and slow down the progression of the disease. Biomarkers have shown great potential as a diagnostic tool in the early diagnosis of many diseases, including AD and PD. However, screening for these biomarkers usually includes invasive, complex and expensive methods such as cerebrospinal fluid (CSF) sampling through a lumbar puncture. Researchers are continuously seeking to find a simpler and more reliable diagnostic tool that would be less invasive than CSF sampling. Saliva has been studied as a potential biological fluid that could be used in the diagnosis and early screening of neurodegenerative diseases. This review aims to provide an insight into the current literature concerning salivary biomarkers used in the diagnosis of AD and PD. The most commonly studied salivary biomarkers in AD are β-amyloid1-42/1-40 and TAU protein, as well as α-synuclein and protein deglycase (DJ-1) in PD. Studies continue to be conducted on this subject and researchers are attempting to find correlations between specific biomarkers and early clinical symptoms, which could be key in creating new treatments for patients before the onset of symptoms.

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