Contents
Special Issue Topic

Artificial Intelligence for Precision Oncology

Guest Editors

Dr. Alfonso Reginelli E-Mail

Associate Professor, Department of Precision Medicine, University of Campania

Dr. Valerio Nardone E-Mail

Associate Professor, Department of Precision Medicine, University of Campania

About the Special lssue

Recently, precision oncology has seen raised interest, thanks to the huge advances in technologies and knowledge of both the human body and cancer disease.

Precision Oncology requires the molecular profiling of tumors to identify targetable alterations, and is rapidly developing and has entered the mainstream of clinical practice.

In this context, precision oncology represents an opportunity to provide far more tailored treatments, taking into consideration that particular attributes and characteristics are unique for patients.

In the fields of imaging, that involve both radiology and radiation oncology, the corresponding concept is represented by the image-guided precision medicine, defined as the use of any form of medical imaging to plan, perform, and evaluate procedures and interventions.

The cross-sectional digital imaging modalities magnetic resonance imaging (MRI) and computed tomography (CT) are the most commonly used modalities of image-guided therapy. These procedures are also supported by ultrasound, angiography, surgical navigation equipment, tracking tools, and integration software.

At the same time, recent developments in radiotherapy with the incorporation of intensity-modulated radiotherapy, molecular imaging-guided radiotherapy, adaptive radiotherapy, and proton therapy have always included image-guided approaches in the clinical workflow.

Last (but not least), artificial intelligence can also be included in this context, as a method that is reshaping the existing scenario of precision oncology, aiming at integrating the large amount of data derived from multi-omics analyses with current advances in high-performance computing and groundbreaking deep-learning strategies. 

For this Special Issue, we welcome basic translational and clinical research papers, cancer biomarkers, professional opinions, and reviews in the broad field of Artificial Intelligence for Precision Oncology in the following categories: CNS; Head and neck; Breast; Hematology; Upper GI (oesophagus, stomach, pancreas, liver); Lung; Gynaecological (endometrium, cervix, vagina, vulva); Lower GI (colon, rectum, anus); Non-prostate urology; Prostate; Sarcoma; Skin cancer/malignant melanoma; Palliation; Pediatric tumours and Elderly oncology.

Keywords: Precision oncology; artificial intelligence; radiomics; radiotherapy; radiology; precision medicine

Published Articles

Open Access Perspective
Artificial intelligence and classification of mature lymphoid neoplasms
Joaquim Carreras ... Naoya Nakamura
Published: April 23, 2024 Explor Target Antitumor Ther. 2024;5:332–348
2857 52 5
Open Access Original Article
Quantitative peritumoral magnetic resonance imaging fingerprinting improves machine learning-based prediction of overall survival in colorectal cancer
Azadeh Tabari ... Dania Daye
Published: February 19, 2024 Explor Target Antitumor Ther. 2024;5:74–84
1679 25 2
Open Access Review
Current implications and challenges of artificial intelligence technologies in therapeutic intervention of colorectal cancer
Kriti Das ... Chakresh Kumar Jain
Published: December 27, 2023 Explor Target Antitumor Ther. 2023;4:1286–1300
2523 34 5
Open Access Systematic Review
Current role of artificial intelligence in head and neck cancer surgery: a systematic review of literature
Antonella Loperfido ... Gianluca Bellocchi
Published: October 24, 2023 Explor Target Antitumor Ther. 2023;4:933–940
2836 47 9
Open Access Perspective
Artificial intelligence ethics in precision oncology: balancing advancements in technology with patient privacy and autonomy
Bahareh Farasati Far
Published: August 31, 2023 Explor Target Antitumor Ther. 2023;4:685–689
2562 54 15
Open Access Review
Emerging role of quantitative imaging (radiomics) and artificial intelligence in precision oncology
Ashish Kumar Jha ... Andre Dekker
Published: August 24, 2023 Explor Target Antitumor Ther. 2023;4:569–582
3148 35 12
Open Access Review
Current role of machine learning and radiogenomics in precision neuro-oncology
Teresa Perillo ... Andrea Manto
Published: July 19, 2023 Explor Target Antitumor Ther. 2023;4:545–555
2199 43 0
Open Access Review
Increasing differential diagnosis between lipoma and liposarcoma through radiomics: a narrative review
Raffaele Natella ... Antonella Santone
Published: June 30, 2023 Explor Target Antitumor Ther. 2023;4:498–510
4558 55 5
Open Access Review
Artificial intelligence and radiomics in magnetic resonance imaging of rectal cancer: a review
Giuseppe Di Costanzo ... Enrico Cavaglià
Published: June 30, 2023 Explor Target Antitumor Ther. 2023;4:406–421
2636 44 7
Open Access Review
Role of artificial intelligence in oncologic emergencies: a narrative review
Salvatore Claudio Fanni ... Emanuele Neri
Published: April 28, 2023 Explor Target Antitumor Ther. 2023;4:344–354
2587 46 5
Open Access Original Article
Development and validation of an infrared-artificial intelligence software for breast cancer detection
Enrique Martín-Del-Campo-Mena ... Yessica González-Mejía
Published: April 27, 2023 Explor Target Antitumor Ther. 2023;4:294–306
3823 50 2
Open Access Review
Artificial intelligence applications in pediatric oncology diagnosis
Yuhan Yang ... Yuan Li
Published: February 28, 2023 Explor Target Antitumor Ther. 2023;4:157–169
3114 60 12
Open Access Original Article
Artificial intelligence fusion for predicting survival of rectal cancer patients using immunohistochemical expression of Ras homolog family member B in biopsy
Tuan D. Pham ... Xiao-Feng Sun
Published: February 07, 2023 Explor Target Antitumor Ther. 2023;4:1–16
2218 41 6
Open Access Review
Artificial intelligence in breast cancer imaging: risk stratification, lesion detection and classification, treatment planning and prognosis—a narrative review
Maurizio Cè ... Michaela Cellina
Published: December 27, 2022 Explor Target Antitumor Ther. 2022;3:795–816
5057 100 17
Open Access Systematic Review
Diffusion-weighted imaging and apparent diffusion coefficient mapping of head and neck lymph node metastasis: a systematic review
Maria Paola Belfiore ... Salvatore Cappabianca
Published: December 13, 2022 Explor Target Antitumor Ther. 2022;3:734–745
4260 43 4