Trace4Research™
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Trace4Research™ is our proprietary platform based on Artificial Intelligence and Data/Image Analytics

log Trace4Research™
Product Sheet

With our proprietary platforms for healthcare, we give value to real-world clinical data and images stored and updated in archives, docs, databases, machine log data, and collected from medical devices in the visible and invisible spectrum.

Trace4Research™ is a proprietary platform based on Artificial Intelligence (AI) and Data/Image Analytics for statistical analysis, automatic classification and development of AI predictive models in health at both single subject and population level.


Trace4Research™ includes proprietary and open-access software to enable:

  1. View, annotation, analysis and archiving of medical images and clinical data;

  2. Development of predictive models based on AI and medical images/clinical data;

  3. View data/images and results of predictive models explaining the mechanism of AI models and their performance.


Highly specialized algorithms based on Machine Learning, Deep Learning, Transfer Learning, Big Data Analytics and Mining, Image Processing, Image Analytics and Mining (including Radiomics) are offered as support to non-apecialized users in a user-friendly and robust way, following a very simple workflow and usability.


Trace4Research™ has been validated and used as software component to train and test several AI models embedded in our Trace4-familiy products, for a variety of clinical diseases, including neurodegenerative and cancer diseases.

Scientific Bibliography

Feb 24

X-RAYS RADIOMICS-BASED MACHINE LEARNING CLASSIFICATION OF ATYPICAL CARTILAGINOUS TUMOUR AND HIGH-GRADE CHONDROSARCOMA OF LONG BONES

Gitto, S., Annovazzi, A., Nulle, K., Interlenghi, M., Salvatore, C., Anelli, V., Baldi, J., Messina, C., Albano, D., Di Luca, F., Armiraglio, E., Parafioriti, A., Luzzati, A., Biagini, R., Castiglioni, I., & Sconfienza, L. M. (2024). X-rays radiomics-based machine learning classification of atypical cartilaginous tumour and high-grade chondrosarcoma of long bones. EBioMedicine, 101, 105018. https://doi.org/10.1016/j.ebiom.2024.105018

Jun 23

MRI radiomics-based machine learning for classification of deep-seated lipoma and atypical lipomatous tumor of the extremities 

Gitto, S., Interlenghi, M., Cuocolo, R., Salvatore, C., Giannetta, V., Badalyan, J., Gallazzi, E., Spinelli, M. S., Gallazzi, M., Serpi, F., Messina, C., Albano, D., Annovazzi, A., Anelli, V., Baldi, J., Aliprandi, A., Armiraglio, E., Parafioriti, A., Daolio, P. A., Luzzati, A., Biagini, R., Castiglioni, I., & Sconfienza, L. M. (2023). MRI radiomics-based machine learning for classification of deep-seated lipoma and atypical lipomatous tumor of the extremities. La Radiologia Medica, 128(8), 989–998. https://doi.org/10.1007/s11547-023-01657-y

Jan 23

MRI RADIOMICS-BASED MACHINE LEARNING FOR CLASSIFICATION OF DEEP-SEATED LIPOMA AND ATYPICAL LIPOMATOUS TUMOR OF THE EXTREMITIES [publication pdf] [publication website]

AUTHORS: Gitto, S., Interlenghi, M., Cuocolo, R., Salvatore, C., ... Castiglioni, I., & Sconfienza, L.M. 

JOURNAL: La Radiologia Medica (Springer) 

doi: 10.1007/s11547-023-01657-y

Jan 23

MRI-BASED ARTIFICIAL INTELLIGENCE TO PREDICT INFECTION FOLLOWING TOTAL HIP ARTHROPLASTY FAILURE [publication website]

AUTHORS: Albano, D., Gitto, S., Messina, C., Serpi, F., Salvatore, C., Castiglioni, I., Zagra, L., De Vecchi, E., Sconfienza, L. M.

JOURNAL: La Radiologia Medica

Jan 22

DEVELOPMENT AND VALIDATION OF AN AI-DRIVEN MAMMOGRAPHIC BREAST DENSITY CLASSIFICATION TOOL BASED ON RADIOLOGIST CONSENSUS [publication pdf] [publication website]

AUTHORS: Magni, V.*, Interlenghi M.*, Cozzi, A., Alì, M., Salvatore C., Azzena, A., ... & Sardanelli, F.

JOURNAL: Radiology

Jan 22

A COMBINED DEEP LEARNING SYSTEM FOR AUTOMATIC DETECTION OF “BOVINE” AORTIC ARCH ON COMPUTED TOMOGRAPHY SCANS [publication pdf] [publication website]

AUTHORS: Secchi, F., Interlenghi, M., Alì, M., Schiavon, E., Monti, C.B., Capra, D., Salvatore, C., ... & Marrocco-Trischitta, M.M.

JOURNAL: Applied Sciences

Jan 21

ARTIFICIAL INTELLIGENCE APPLIED TO CHEST X-RAY FOR DIFFERENTIAL DIAGNOSIS OF COVID-19 PNEUMONIA [publication pdf] [publication website]

AUTHORS: Salvatore, C., Interlenghi, M., Monti, C. B., Ippolito, D., Capra, D., Cozzi, A., Schiaffino, S., Polidori, A., Gandola, D., Alì, M., Castiglioni, I., Messa, C., & Sardanelli, F.

JOURNAL: Diagnostics

Jan 21

AI APPLICATIONS TO MEDICAL IMAGES: FROM MACHINE LEARNING TO DEEP LEARNING [publication pdf] [publication website]

AUTHORS: Castiglioni, I., Rundo, L., Codari, M., Di Leo, G., Salvatore, C., Interlenghi, M., ... & Sardanelli, F.

JOURNAL: Physica Medica

Jan 21

MACHINE LEARNING APPLIED ON CHEST X-RAY CAN AID IN THE DIAGNOSIS OF COVID-19: A FIRST EXPERIENCE FROM LOMBARDY, ITALY [preprint] [publication pdf] [publication website]

AUTHORS: Castiglioni, I., Ippolito, D., Interlenghi, M., Monti, C. B., Salvatore, C., Schiaffino, S., ... & Sardanelli, F.

JOURNAL: European Radiology Experimental

Jan 20

PREDICTING OUTCOME OF ACQUIRED BRAIN INJURY BY THE EVOLUTION OF PAROXYSMAL SYMPATHETIC HYPERACTIVITY SIGNS [publication website]

AUTHORS: Lucca, L., De Tanti, A., Cava, F., Romoli, A.M., Formisano, R., Scarponi, F., Estraneo, A., Frattini, D., Tonin, P., Bertolino, C., Salucci, P., Hakiki, B., D’Ippolito, M., Zampolini, M., Masotta, O., Premoselli, S., Interlenghi, M., Salvatore, C., Polidori, A., & Cerasa, M. 

JOURNAL: Journal of Neurotrauma