Chongfan Technology
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01
2024
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Medical diagnosis technology based on "infrared spectroscopy machine learning" can realize universal health screening
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According to Maims Consulting, infrared spectroscopy is increasingly becoming an in vitro diagnostic test because it can detect the molecular signature spectrum of a variety of biomarkers. However, according to a study by the University of Munich (München) and the Max Planck Institute for Optics (MPQ), what is missing is the application of "infrared spectral fingerprinting" to large-scale natural variation.
The research project, the Broadband Infrared Diagnostics (BIRD) Center at the University of Munich, aims to evaluate whether combining infrared spectral fingerprinting and machine learning can produce a single-measurement multi-phenotype medical diagnostic platform. Related research papers published inCell Reports MedicineJournal.
The study builds on previous research by the University of Munich and the Max Planck Institute for Quantum Optics, using infrared spectroscopy to monitor blood components for medical diagnostic purposes. In 2021, the two institutions studied whether molecular infrared spectral fingerprints created from blood samples by Fourier transform infrared (FTIR) spectroscopy would change over time, an important consideration before proposing to use the data for human health monitoring. The infrared spectral information was found to be "very stable" given the natural variations in most people's normal lifestyles.
Tarek Eissa, first author of the paper, analyzed thousands of molecular infrared spectral fingerprints.
The new work applied Fourier transform infrared spectroscopy to 5184 blood samples from 3169 individuals in a German comprehensive health research project. The researchers used machine learning to decode the measured infrared spectra, looking for signs of dyslipidemia, hypertension, type 2 diabetes and other common diseases.
"To the best of our knowledge, our work uses infrared spectral fingerprinting to analyze the largest population currently available and aims to examine the ability of this method to comprehensively detect several medically relevant human health phenotypes." The paper published by the project commented, "Previous clinical spectroscopy studies have generally relied on rather small patient populations, which hinders the potential for developing infrared spectroscopy-based medical diagnostic models that can be skillfully generalized to larger populations."
The researchers said: "Our success shows that the combination of infrared spectral fingerprinting and machine learning can accurately identify sub-healthy individuals and describe chronic multiple disease states. The data also show that the method is able to predict disease before health problems become apparent."
"This new method can not only identify one condition at a time, but also accurately identify a series of health problems." The University of Munich pointed out, "This medical diagnostic system driven by machine learning can not only identify healthy individuals, but also detect complex conditions involving multiple diseases at the same time. In addition, it can predict the development of metabolic syndrome years before symptoms appear, providing a window for early intervention."
The team commented that while it remains to be seen whether infrared spectral fingerprinting can decode health trajectories over a decadal time period, the new study has validated the technology in a large-scale population-level study and points out that molecular infrared fingerprinting will be an regular part of universal health screening. This is especially important for metabolic disorders such as cholesterol abnormalities and diabetes, where timely intervention can significantly improve treatment outcomes.
"The combination of infrared spectroscopy and machine learning will transform health diagnostics." The University of Munich said, "With just a blood sample, a powerful new tool can be used to monitor our health, detect problems more effectively, and have the potential to improve global healthcare."
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