Before the first symptoms of Alzheimer's disease appears some alternations in the brain can cause little changes in eye movement patterns, gait patterns, face recognition patterns...AI can recognize these changes early and identify patients at risk of developing the most severe forms of dementia. AI see some changes that humans can't see ( even it's too complex) but can also monitoring the patient and whith these patterns the doctor can follow the progression and efficiency of his treatment or prevention therapy. Also for patients who have already AD doctors can use the device for adjustments. When a doctor or radiologist reads scans from PET,MRI it is impossible wheter a person will progress AD or dementia and his subtypes. AI can also predict the severity of the disease in different patients. For drug companies it is very difficult to identify the wright patient. With computational pathology and pattern recognition technics we can make better diagnosis and less misdiagnosis.
Early stage screening of Alzheimer's disease by detecting subtypes of MCI...with a normal webcam POC.
A reliable and inexpensive diagnostic test that can be used in any doctor's office all over the world....
AI 4.0...A decision making tool for GP's ( General Practitioner ) Nature.com
THERE IS A BIG DIFFERENCE BETWEEN A BIOLOGICAL BIOMARKER FOR ALZHEIMER'S DISEASE AND A DIGITAL BIOMARKER...
Biological Biomarker for Alzeimer's: can be a toxic protein like amyloid or TAU
Digital biomarker: can give you data about the function of different parts of your brain
Only with digital biomarkers you can make a differentation between Alzheimer's disease and other neurodegenerative diseases preclinical...like Lewy Body dementia with 80% misdiagnosis and 50% get a diagnosis of Alzheimer's disease
The reason why 99,6% of all Alzheimer's drugs fail...even with neurons without any plaques...we still have an old neuron with low neuroplasticity and low communication...New neurons Archive Old memories...
Imaging biomarkers (PET imaging of amyloid and tau aggregates) and CSF markers (measurement of amyloid and tau) are very helpful to identify AD pathophysiology, but are unlikely to be a routine diagnostic tool: PET technique is only accessible in specialized departments and is very expensive; lumbar puncture may be regarded as invasive, complicated, and time consuming by many physicians.
The hope is to diagnose Alzheimer’s disease before the symptoms start. Future treatments could then target the disease in its earliest stages before irreversible brain damage or mental decline occurs. The development of marker panels is in its early stages and requires further substantial preclinical and clinical validation. It seems likely that only a combined analysis of several biomarkers will define a patient-specific signature to diagnose AD in the future. The respective diagnostic and prognostic markers of AD are expected to improve patients’ outcome significantly and to support the discovery of new treatment targets. Compared with neuroimaging or collection of CSF, it is important for biomarkers to be cost-effective and time consuming.
It is important to identify more specific and more sensitive AD biomarkers that can not only accurately diagnose early-stage AD but also differentiate AD from non-AD dementias (vascular dementia, tauopathy, frontotemporal dementia, Lewy body dementia, etc.). These biomarkers should be able to assess the risk of AD in combination with other known risk factors, facilitate screening of potential therapeutic agents and their identification, track the prodromal stages of AD, guide therapeutic decision-making, and monitor therapeutic efficacy
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