We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
LGC Clinical Diagnostics

Download Mobile App


24 Feb 2024 - 28 Feb 2024
05 Mar 2024 - 07 Mar 2024

Biosensing Platform Combined with Machine Learning to Enable Minimally-Invasive Detection of Alzheimer's

By LabMedica International staff writers
Posted on 28 Oct 2022
Print article
Image: Researchers are exploring the use of ML for a minimally invasive system to detect Alzheimer\'s disease (Photo courtesy of NIH)
Image: Researchers are exploring the use of ML for a minimally invasive system to detect Alzheimer\'s disease (Photo courtesy of NIH)

Alzheimer's disease is a severe neurodegenerative disorder characterized by progressive memory, cognitive impairment and personality changes, which can further evolve to dementia and death. Early detection allows doctors to give timely treatments and interventions for the patient. Currently, doctors rely on several biomarkers - substances in an organism that can indicate the existence of a disease or condition - to detect Alzheimer's disease. However, collecting data that inform about these biomarkers is expensive and can be time-consuming. Now, a machine learning system being developed could provide a minimally invasive approach for detecting Alzheimer's disease as early as possible.

A team of researchers led by Penn State (University Park, PA, USA) has received a USD 1.2 million grant from the National Institutes of Health (NIH, Bethesda, MD, USA) to help fund a project to develop a machine learning system for early Alzheimer’s disease detection. The research team plans to design a system that utilizes a variety of biosensors, including optical, mechanical and electrochemical nano-sensors, that can analyze biological samples. According to the researchers, biosensing data matches well with the capabilities of machine learning techniques and the combination of the two technologies could even pave the way to new discoveries for other conditions and disease. Currently, the team is analyzing animal biological samples, but, if these initial inquiries prove successful, the researchers will move on to study human biological samples.

“By integrating a multimodal biosensing platform and a machine learning framework, we expect the system to improve early detection of Alzheimer's disease and enhance AD detection accuracy,” said Fenglong Ma, assistant professor of information sciences and technology and Institute for Computational and Data Sciences co-hire. “The biosensing platform will generate different types of sensing data, and machine learning aims to analyze these data to predict Alzheimer’s in the early stage. Since the sensing data are so diverse - or heterogeneous - advanced machine learning techniques can help model such data. Also, machine learning may help us identify some new AD biomarkers.”

“Given different types of sensing data, for instance, data acquired from different biochemical markers in human body fluids, machine learning can perform feature selection and establish associations between an individual biomarker and Alzheimer's disease, or between a set of biomarkers and the disease,” said Sharon Huang, professor of information sciences and technology and Huck Institutes of the Life Sciences co-hire. “We hope our project can result in a minimally-invasive technique that can detect Alzheimer's disease in its early stages. The technique also has the potential to be high throughput, making it possible to be used in screening for the disease. We will also try our best to make the technique accurate, reducing false positives and false negatives in AD detection.”

Related Links:
Penn State

Platinum Member
COVID-19 Rapid Test
OSOM COVID-19 Antigen Rapid Test
Complement 3 (C3) Test
GPP-100 C3 Kit
Gold Member
Turbidimetric Control
D-Dimer Turbidimetric Control

Print article


Clinical Chemistry

view channel
Image: Wireless Point-of-Care Testing for Hepatitis B Virus (Photo courtesy of Chulalongkorn University)

Wireless Hepatitis B Test Kit Completes Screening and Data Collection in One Step

Hepatitis B, a significant global health concern, is responsible for chronic liver diseases like cirrhosis and liver cancer which is one of the most common cancers worldwide. The challenge with hepatitis... Read more

Molecular Diagnostics

view channel
Image: Aptiva utilizes particle-based multi-analyte technology (PMAT) (Photo courtesy of Werfen)

Novel Immunoassays Enable Early Diagnosis of Antiphospholipid Syndrome

Antiphospholipid syndrome (APS) is an autoimmune disorder that typically presents as venous or arterial thrombosis and/or pregnancy loss. Diagnosing APS can be difficult as its symptoms often resemble... Read more


view channel
Image: The Gazelle Hb Variant Test (Photo courtesy of Hemex Health)

First Affordable and Rapid Test for Beta Thalassemia Demonstrates 99% Diagnostic Accuracy

Hemoglobin disorders rank as some of the most prevalent monogenic diseases globally. Among various hemoglobin disorders, beta thalassemia, a hereditary blood disorder, affects about 1.5% of the world's... Read more


view channel
Image: The photoacoustic spectral response sensing instrument is based on low-cost laser diodes (Photo courtesy of Khan et al., doi 10.1117/1.JBO.29.1.017002)

Compact Photoacoustic Sensing Instrument Enhances Biomedical Tissue Diagnosis

The pursuit of precise and efficient diagnostic methods is a top priority in the constantly evolving field of biomedical sciences. A promising development in this area is the photoacoustic (PA) technique.... Read more


view channel
Image: The companies will develop genetic testing systems based on capillary electrophoresis sequencers (Photo courtesy of 123RF)

Sysmex and Hitachi Collaborate on Development of New Genetic Testing Systems

Sysmex Corporation (Kobe, Japan) and Hitachi High-Tech Corporation (Tokyo, Japan) have entered into a collaboration for the development of genetic testing systems using capillary electrophoresis sequencers... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.