The authors begin a discussion of the statistical tools available to compare and correlate two or more data sets.
From Classical Regression to AI and Beyond: The Chronicles of Calibration in Spectroscopy: Part I
February 14th 2025This “Chemometrics in Spectroscopy” column traces the historical and technical development of these methods, emphasizing their application in calibrating spectrophotometers for predicting measured sample chemical or physical properties—particularly in near-infrared (NIR), infrared (IR), Raman, and atomic spectroscopy—and explores how AI and deep learning are reshaping the spectroscopic landscape.
Improving Citrus Quality Assessment with AI and Spectroscopy
February 13th 2025Researchers from Jiangsu University review advancements in computer vision and spectroscopy for non-destructive citrus quality assessment, highlighting the role of AI, automation, and portable spectrometers in improving efficiency, accuracy, and accessibility in the citrus industry.
Advancing Near-Infrared Spectroscopy and Machine Learning for Personalized Medicine
February 12th 2025Researchers have developed a novel approach to improve the accuracy of near-infrared spectroscopy (NIRS or NIR) in quantifying highly porous, patient-specific drug formulations. By combining machine learning with advanced Raman imaging, the study enhances the precision of non-destructive pharmaceutical analysis, paving the way for better personalized medicine.
New Method for Detecting Fentanyl in Human Nails Using ATR FT-IR and Machine Learning
February 11th 2025Researchers have successfully demonstrated that human nails can serve as a reliable biological matrix for detecting fentanyl use. By combining attenuated total reflectance-Fourier transform infrared (ATR FT-IR) spectroscopy with machine learning, the study achieved over 80% accuracy in distinguishing fentanyl users from non-users. These findings highlight a promising, noninvasive method for toxicological and forensic analysis.
New AI-Powered Raman Spectroscopy Method Enables Rapid Drug Detection in Blood
February 10th 2025Scientists from China and Finland have developed an advanced method for detecting cardiovascular drugs in blood using surface-enhanced Raman spectroscopy (SERS) and artificial intelligence (AI). This innovative approach, which employs "molecular hooks" to selectively capture drug molecules, enables rapid and precise analysis, offering a potential advance for real-time clinical diagnostics.