Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry

N Verbeeck, RM Caprioli… - Mass spectrometry …, 2020 - Wiley Online Library
Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that
can map the spatial distribution of molecules with high chemical specificity. IMS does not …

Applications of MALDI-TOF mass spectrometry in clinical proteomics

V Greco, C Piras, L Pieroni, M Ronci… - Expert review of …, 2018 - Taylor & Francis
Introduction: The development of precision medicine requires advanced technologies to
address the multifactorial disease stratification and to support personalized treatments …

Critical review of surface-enhanced Raman spectroscopy applications in the pharmaceutical field

J Cailletaud, C De Bleye, E Dumont, PY Sacré… - … of pharmaceutical and …, 2018 - Elsevier
Surface-enhanced Raman spectroscopy (SERS) is a sensitive analytical tool used in the
pharmaceutical field in recent years. SERS keeps all the advantages of classical Raman …

A review on recent machine learning applications for imaging mass spectrometry studies

A Jetybayeva, N Borodinov, AV Ievlev… - Journal of Applied …, 2023 - pubs.aip.org
Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology,
chemistry, and materials science fields that continue to expand. IMS provides a qualitative …

A review of pharmaceutical robot based on hyperspectral technology

X Su, Y Wang, J Mao, Y Chen, AT Yin, B Zhao… - Journal of intelligent & …, 2022 - Springer
The quality and safety of medicinal products are related to patients' lives and health.
Therefore, quality inspection takes a key role in the pharmaceutical industry. Most of the …

Fighting falsified medicines: the analytical approach

H Rebiere, P Guinot, D Chauvey, C Brenier - Journal of pharmaceutical and …, 2017 - Elsevier
Given the harm to human health, the fight against falsified medicines has become a priority
issue that involves numerous actors. Analytical laboratories contribute by performing …

Characterization of pharmaceutically relevant materials at the solid state employing chemometrics methods

NL Calvo, RM Maggio, TS Kaufman - Journal of pharmaceutical and …, 2018 - Elsevier
The understanding of materials and processes is a requirement when it comes to build
quality into pharmaceutical products. This can be achieved through the development of …

Perioperative margin detection in basal cell carcinoma using a deep learning framework: a feasibility study

AML Santilli, A Jamzad, NNY Janssen… - International Journal of …, 2020 - Springer
Purpose Basal cell carcinoma (BCC) is the most commonly diagnosed cancer and the
number of diagnosis is growing worldwide due to increased exposure to solar radiation and …

Quantitative mass spectrometry imaging using multivariate curve resolution and deep learning: A case study

F Golpelichi, H Parastar - Journal of the American Society for …, 2023 - ACS Publications
In the present contribution, a novel approach based on multivariate curve resolution and
deep learning (DL) is proposed for quantitative mass spectrometry imaging (MSI) as a potent …

Microstructural Characterization of Dry Powder Inhaler Formulations Using Orthogonal Analytical Techniques

G Farias, WJ Ganley, R Price, DS Conti… - Pharmaceutical …, 2024 - Springer
Purpose For locally-acting dry powder inhalers (DPIs), develo** novel analytical tools that
are able to evaluate the state of aggregation may provide a better understanding of the …