Review
Urology & Nephrology
Yuankai Huo, Ruining Deng, Quan Liu, Agnes B. Fogo, Haichun Yang
Summary: The explosive growth of AI technologies, particularly in deep learning, has led to revolutionary applications in AI-assisted healthcare, including in renal pathology. However, successful integration of AI in renal pathology requires close interdisciplinary collaborations between computer scientists and renal pathologists. Understanding the high-level principles of AI technologies and optimizing AI techniques for renal pathology are crucial for future applications in this field.
KIDNEY INTERNATIONAL
(2021)
Article
Environmental Sciences
Takuya Kurihana, Elisabeth J. Moyer, Ian T. Foster
Summary: This study introduces a new analysis approach that uses artificial intelligence to classify satellite cloud observations, reducing the dimensionality of the data and generating a unique cloud dataset. The method captures a greater variety of cloud types and provides rich information for global analysis, contributing to the advancement of climate research.
Article
Radiology, Nuclear Medicine & Medical Imaging
Andrew T. Grainger, Arun Krishnaraj, Michael H. Quinones, Nicholas J. Tustison, Samantha Epstein, Daniela Fuller, Aakash Jha, Kevin L. Allman, Weibin Shi
Summary: Utilizing deep learning methods with a template data augmentation strategy can accurately and rapidly quantify total abdominal subcutaneous and visceral fat.
ACADEMIC RADIOLOGY
(2021)
Article
Telecommunications
Abir Mchergui, Tarek Moulahi, Sherali Zeadally
Summary: Advancements in communications, smart transportation systems, and computer systems have opened up new possibilities for intelligent solutions in traffic safety and convenience. Artificial Intelligence (AI) is currently being utilized in the field of Vehicular Ad hoc NETworks (VANETs) to enhance conventional data-driven methods and improve passenger comfort, safety, and road experience.
VEHICULAR COMMUNICATIONS
(2022)
Article
Biochemical Research Methods
Lalith Kumar Shiyam Sundar, Otto Muzik, Irene Buvat, Luc Bidaut, Thomas Beyer
Summary: State-of-the-art patient management requires investigating both the anatomy and physiology of patients, with hybrid imaging techniques providing both structural and functional information. Artificial intelligence algorithms show promise in facilitating analysis of multi-parametric data in medical imaging, addressing challenges in extracting clinical information from large sets of multi-dimensional imaging data.
Review
Pharmacology & Pharmacy
Junhuang Jiang, Xiangyu Ma, Defang Ouyang, Robert O. Williams
Summary: Artificial Intelligence (AI) plays a crucial role in pharmaceutical formulation development, enabling researchers to better understand and predict drug properties, thus improving the efficiency of product development.
Article
Computer Science, Artificial Intelligence
Munir Ahmad, Sagheer Abbas, Areej Fatima, Taher M. Ghazal, Meshal Alharbi, Muhammad Adnan Khan, Nouh Sabri Elmitwally
Summary: Cattle identification is crucial for managing animal health, traceability, bread classification, and insurance claim verification. Traditional identification methods can be easily circumvented, so the application of biometric identification technology, specifically using muzzle patterns, has shown promising results. This paper proposes a solution to prevent and/or discard fraudulent claims in livestock insurance by intelligently identifying proxy animals.
EGYPTIAN INFORMATICS JOURNAL
(2023)
Article
Biochemistry & Molecular Biology
Norman E. Sharpless, Anthony R. Kerlavage
Summary: Artificial intelligence, machine learning, and deep learning have diverse applications in cancer research and clinical care, and the National Cancer Institute (NCI) is actively involved in supporting and advancing these technologies. In addition to developing and evaluating AI tools, NCI focuses on fostering a culture of data sharing, training the next generation of scientists, promoting interdisciplinary collaborations, and ensuring ethical principles in AI research and technologies.
BIOCHIMICA ET BIOPHYSICA ACTA-REVIEWS ON CANCER
(2021)
Article
Remote Sensing
Shin-nosuke Ishikawa, Masato Todo, Masato Taki, Yasunobu Uchiyama, Kazunari Matsunaga, Peihsuan Lin, Taiki Ogihara, Masao Yasui
Summary: We propose a method called What I Know (WIK) in explainable artificial intelligence (XAI) to provide additional information for verifying the reliability of deep learning models. This method demonstrates an instance in the training dataset that is similar to the input data to be inferred in a remote sensing image classification task. It helps determine whether the training dataset is sufficient for each inference and validates the validity of the model's inferences by checking the selected example data.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Biochemical Research Methods
Andreas Holzinger, Katharina Keiblingera, Petr Holub, Kurt Zatloukal, Heimo Mueller
Summary: Due to the successes of AI, such as ChatGPT, and the combination of biotechnology, new potential solutions have emerged to address global problems and contribute to sustainability.
Article
Public, Environmental & Occupational Health
Hao Li, Xiang Tao, Tuo Liang, Jie Jiang, Jichong Zhu, Shaofeng Wu, Liyi Chen, Zide Zhang, Chenxing Zhou, Xuhua Sun, Shengsheng Huang, Jiarui Chen, Tianyou Chen, Zhen Ye, Wuhua Chen, Hao Guo, Yuanlin Yao, Shian Liao, Chaojie Yu, Binguang Fan, Yihong Liu, Chunai Lu, Junnan Hu, Qinghong Xie, Xiao Wei, Cairen Fang, Huijiang Liu, Chengqian Huang, Shixin Pan, Xinli Zhan, Chong Liu
Summary: In this study, a comprehensive artificial intelligence (AI) tool was developed for the diagnosis and prediction of ankylosing spondylitis (AS). The tool demonstrated impressive performance, surpassing that of human experts, and a clinical prediction model was established for accurate categorization of high-risk and low-risk AS patients.
FRONTIERS IN PUBLIC HEALTH
(2023)
Review
Engineering, Industrial
Chandan K. Sahu, Crystal Young, Rahul Rai
Summary: Augmented reality (AR) is valuable in manufacturing for tasks like assembly and maintenance, but current strategies rely on traditional non-AI methods. The incorporation of AI strategies like deep learning can greatly enhance classical AR methods. Future research should focus on exploring AI strategies for improving AR systems in broader scene variations.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Review
Computer Science, Artificial Intelligence
Bahram Jalali, Yiming Zhou, Achuta Kadambi, Vwani Roychowdhury
Summary: Physics has been successful in explaining nature using low-dimensional deterministic models, while artificial intelligence (AI) has achieved astonishing performance in domains like image classification and speech recognition through data-driven computational frameworks. However, AI's inconsistent predictions and computational complexity conflict with Moore's Law. This paper discusses how a symbiosis of physics and AI can overcome these challenges.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
(2022)
Review
Ophthalmology
Cristina Gonzalez-Gonzalo, Eric F. Thee, Caroline C. W. Klaver, Aaron Y. Lee, Reinier O. Schlingemann, Adnan Tufail, Frank Verbraak, Clara Sanchez
Summary: This study focuses on the importance of trustworthy AI in ophthalmology and identifies the key aspects and challenges that need to be considered in the design pipeline to generate trustworthy AI systems. Stakeholders' roles and responsibilities are defined, and a collaborative approach is emphasized for the potential benefits of AI to be realized in real-world ophthalmic settings.
PROGRESS IN RETINAL AND EYE RESEARCH
(2022)
Review
Health Care Sciences & Services
Ruopeng An, Jing Shen, Yunyu Xiao
Summary: This scoping review provides an overview of the applications of artificial intelligence (AI) in obesity research, with a focus on machine learning (ML) and deep learning (DL) models applied to tabular, image, and text data. The review identifies the usefulness of AI models in detecting meaningful patterns and relationships related to obesity outcomes. Additionally, it discusses the increasing trend of adopting state-of-the-art DL models for challenging tasks in computer vision and natural language processing.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Carlo C. Quattrocchi, Marco Parillo, Federica Spani, Doriana Landi, Gaia Cola, Caterina Dianzani, Eleonora Perrella, Girolama A. Marfia, Carlo A. Mallio
Summary: This study aimed to assess the presence of detectable changes in skin thickness on brain MRI scans in patients with MS, a history of GBCAs administrations, and evidence of gadolinium deposition in the brain. Qualitative and quantitative assessment of skin thickness revealed significant differences between patients with and without evidence of gadolinium deposition.
INVESTIGATIVE RADIOLOGY
(2023)
Article
Clinical Neurology
Valeria Pozzilli, Massimo Marano, Alessandro Magliozzi, Carlo Augusto Mallio, Daniele Marruzzo, Francesca Romana Barbieri, Vincenzo Di Lazzaro, Riccardo Antonio Ricciuti
Summary: Deep brain stimulation (DBS) is an effective treatment for movement disorders such as Holmes tremor (HT). The ideal target for DBS in HT is still uncertain. Advanced neuroimaging techniques can help identify the target and achieve almost complete tremor suppression, providing new treatment options.
NEUROLOGICAL SCIENCES
(2023)
Article
Orthopedics
Carlo. A. A. Mallio, Federico Greco, Francesco Gaudino, Bruno Beomonte Zobel, Carlo. C. C. Quattrocchi
Summary: This study aimed to evaluate bone density changes at the level of normal trabecular bone and bone metastases (BMs) after denosumab (DM) treatment in oncologic patients. The results showed that DM treatment can progressively increase CT bone density in both normal trabecular bone and BMs, with a more pronounced effect on osteolytic metastases.
SKELETAL RADIOLOGY
(2023)
Review
Chemistry, Multidisciplinary
Federico Greco, Bruno Beomonte Zobel, Gianfranco Di Gennaro, Carlo Augusto Mallio
Summary: Advances in understanding the oncogenesis of renal cell carcinoma (RCC) have resulted in the development of immune checkpoint inhibitors (ICIs), improving clinical outcomes for patients with metastatic RCC (mRCC). Our literature search identified studies in RECIST criteria, radiomics and artificial intelligence, atypical response patterns, and body composition. These studies provide novel data that aim to enhance patient management and clinical outcomes, further supporting the concept of precision medicine. Radiomics and artificial intelligence can non-invasively obtain data that is not visible to the naked eye, offering potential advantages for predicting treatment response and personalized therapeutic approaches. This literature review focuses on the role of computed tomography (CT) in evaluating and predicting the effects of ICIs on mRCC patients using radiomics and artificial intelligence.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Claudia Lucia Piccolo, Carlo Augusto Mallio, Laura Messina, Manuela Tommasiello, Paolo Orsaria, Vittorio Altomare, Matteo Sammarra, Bruno Beomonte Zobel
Summary: This study evaluated the radiological features of B3 lesions in patients with genetic mutations to establish an anatomo-radiological correlation. BRCA1 was the most frequent mutation followed by ATM and BRCA2. LN and FEA showed the highest malignancy correlation. Mammography revealed microcalcifications in 90.5% of lesions, ultrasound detected hypoechoic lesions, and breast MRI detected mass enhancement. DWI and kinetic curves significantly correlated with the risk of cancer. The high malignancy rate suggests surgical excision of B3 lesions.
APPLIED SCIENCES-BASEL
(2023)
Article
Cardiac & Cardiovascular Systems
Carlo A. Mallio, Gianfranco Di Gennaro, Federico Greco, Andrea Pescosolido, Caterina Bernetti, Claudia Lucia Piccolo, Vitaliano Buffa, Carlo C. Quattrocchi, Bruno Beomonte Zobel
Summary: This retrospective study discovered an association between lipomatous hypertrophy of the interatrial septum (LHIS) and visceral adiposity using CT imaging. The study also found that visceral adipose tissue and total adipose tissue were predictors of LHIS area. These findings are important for early identification of LHIS patients at risk for visceral obesity and implementing lifestyle interventions.
Article
Genetics & Heredity
Federico Greco, Andrea Panunzio, Alessandro Tafuri, Caterina Bernetti, Vincenzo Pagliarulo, Bruno Beomonte Zobel, Arnaldo Scardapane, Carlo Augusto Mallio
Summary: GTPases of immunity-associated proteins (GIMAP) genes play an important role in the maintenance and development of lymphocytes and can inhibit tumor development by increasing the amount and activity of immunocytes. This study utilized CT imaging to identify the imaging features of GIMAP expression in ccRCC, which could be used for predicting immunotherapy efficacy and developing targeted therapy.
Review
Oncology
Carlo Augusto Mallio, Caterina Bernetti, Laura Cea, Andrea Buoso, Massimo Stiffi, Daniele Vertulli, Federico Greco, Bruno Beomonte Zobel
Summary: Immune-checkpoint inhibitors (ICIs) are immunomodulatory monoclonal antibodies that enhance the host's anti-tumor immune response and promote T-cell-mediated actions against tumors. However, they can cause immune-related adverse events (irAEs), mainly affecting the skin, gastrointestinal, hepatic, and endocrine systems. Early diagnosis of irAEs is crucial for proper management and treatment adjustments. This review aims to provide guidance on recognizing the significant radiological findings of irAEs based on incidence, severity, and the role of imaging.
Article
Radiology, Nuclear Medicine & Medical Imaging
Carlo A. Mallio, Andrea C. Sertorio, Caterina Bernetti, Bruno Beomonte Zobel
Summary: Structured reporting improves workflow and communication in radiology. Artificial intelligence applications in medicine are rapidly growing, and large language models (LLMs) have gained importance in radiology for structured reporting. We compared four LLMs models in terms of knowledge and template proposal for structured reporting. LLMs have the potential to generate structured reports in radiology, but further formal validation is needed.
Article
Surgery
Marco Parillo, Federica Vaccarino, Carlo Augusto Mallio, Carlo Cosimo Quattrocchi
Summary: This is the first report to describe condylar jugular diverticulum (CJD) using contrast-enhanced computed tomography scan in medical literature. CJD is a rare anatomical variation of the jugular bulb that should be recognized to prevent radiological and surgical errors and to achieve proper pre-surgical planning for skull base pathologies.
INDIAN JOURNAL OF OTOLARYNGOLOGY AND HEAD & NECK SURGERY
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Marco Parillo, Carlo Augusto Mallio, Aart J. van der Molen, Alex Rovira, Ilona A. Dekkers, Uwe Karst, Gerard Stroomberg, Olivier Clement, Eliana Gianolio, Aart J. Nederveen, Alexander Radbruch, Carlo Cosimo Quattrocchi
Summary: This article summarizes the current role of GBCA in MRI RADS, indicating that most RADS require the use of GBCA, especially in MRIs of patients with cancer. However, some RADS may avoid the use of GBCA in the future. Further research is needed to evaluate the impact of high T1 relaxivity GBCA on RADS scoring.
MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Aart J. van der Molen, Carlo C. Quattrocchi, Carlo A. Mallio, Ilona A. Dekkers
Summary: In 2014, visible hyperintensities on brain images were found to be associated with previous GBCA injections and gadolinium deposition. After 10 years, the ESMRMB-GREC reviewed the current state of knowledge on gadolinium retention and deposition.
EUROPEAN RADIOLOGY
(2023)
Article
Hematology
Federico Greco, Bruno Beomonte Zobel, Carlo Augusto Mallio
Summary: Quantitative analysis of abdominal adipose tissue is crucial for understanding prognosis and clinical outcomes in various diseases. Recent studies have focused on the effects of abdominal fat compartments and their changes in distribution after therapies in lymphoma patients. Opportunistic analysis of body composition using computed tomography (CT) images can improve patient management and clinical outcomes through tailored therapies.
HEMATOLOGY REPORTS
(2023)
