10 Dokumente gefunden
Adapting Image‐Based Models for 1D Data via Spider Plot Transformation and Transfer Learning
1D data, such as time series, and spectroscopy contain rich information but pose challenges for machine learning, due to limited large, labeled datasets and absence of specialized pretrained neural networks. Existing 1D analysis methods often rely on traditional chemometric approaches and rarely exploit…
Weinheim: Wiley-VCH Verlag, 2025-12-12
Broadband coherent Raman microspectroscopy for the investigation of head and neck cancer advancing ultrafast spectral histopathology
aus: Discover Imaging
Abstract Nonlinear spectroscopic imaging techniques such as coherent Raman scattering (CRS) have proven to be powerful tools for biomedical research, providing multifaceted imaging data that holds great potential for medical diagnostics and therapy. Among these, broadband implementations such as broadband…
Singapore: Springer Nature Singapore, 2025-10-23
A Systematic Investigation of Image Pre-Processing on Image Classification
AI-powered image analysis is a transformative technology with immense potential to enhance diagnostics and patient care. Accurate medical image assessment plays a crucial role in disease detection and treatment planning, yet challenges arise due to noise and visual variations in medical imaging. Image…
A Review on Data Fusion of Multidimensional Medical and Biomedical Data
Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characterization of samples and might improve clinical diagnosis…
Basel: MDPI, 2022-11-02
Label‐free differentiation of clinical E. coli and Klebsiella isolates with Raman spectroscopy
Raman spectroscopy is a promising spectroscopic technique for microbiological diagnostics. In routine diagnostic, the differentiation of pathogens of the Enterobacteriaceae family remain challenging. In this study, Raman spectroscopy was applied for the differentiation of 24 clinical E. coli , Klebsiella…
Weinheim: WILEY‐VCH Verlag GmbH & Co. KGaA, 2022-07-05
Data science and machine learning for spectral data
Content: Photonics for the unment medical need; Photonic technologies; Data life cycle and machine learning; Photonic Data Science; Artifical Intelligence; Feature extraction; Dimension reduction; Example of spectral scans; MALDI spectrometric imaging data preprocessing; Raman spectroscopy for sepsis…
Detection of multi-resistant clinical strains of E. coli with Raman spectroscopy
Abstract In recent years, we have seen a steady rise in the prevalence of antibiotic-resistant bacteria. This creates many challenges in treating patients who carry these infections, as well as stopping and preventing outbreaks. Identifying these resistant bacteria is critical for treatment decisions…
Berlin, Heidelberg: Springer, 2022-02
Biochemical Analysis of Leukocytes after In Vitro and In Vivo Activation with Bacterial and Fungal Pathogens Using Raman…
Biochemical information from activated leukocytes provide valuable diagnostic information. In this study, Raman spectroscopy was applied as a label-free analytical technique to characterize the activation pattern of leukocyte subpopulations in an in vitro infection model. Neutrophils, monocytes, and…
Basel: Molecular Diversity Preservation International, 2021-09-28
Investigations on chemometric approaches for diagnostic applications utilizing various combinations of spectral and image…
In the presented work, several data fusion and machine learning approaches were explored within the frame of the data combination for various measurement techniques in biomedical applications. For each of the measurement techniques used in this work, the data was ana-lyzed by means of machine learning.…