Article
Computer Science, Artificial Intelligence
Alberto Nogales, Alvaro J. Garcia-Tejedor, Diana Monge, Juan Serrano Vara, Cristina Anton
Summary: Artificial intelligence, with deep learning being the most impactful technique, plays a significant role in the medical field where complex data and crucial decisions by doctors are involved. A systematic review conducted by a multidisciplinary team identified the increasing number of publications on deep learning in medicine, with convolutional neural networks being the most commonly used models, especially in oncology for image analysis.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Francesco Piccialli, Vittorio Di Somma, Fabio Giampaolo, Salvatore Cuomo, Giancarlo Fortino
Summary: New technologies are revolutionizing medicine, with a key role played by data. Artificial intelligence, especially Deep Learning, is well-suited to handle the exponential growth of health-related information in the field of medicine, helping to build optimal neural networks for clinical problems as the amount of training data increases.
INFORMATION FUSION
(2021)
Review
Medicine, General & Internal
Nora El-Rashidy, Samir Abdelrazik, Tamer Abuhmed, Eslam Amer, Farman Ali, Jong-Wan Hu, Shaker El-Sappagh
Summary: The study identifies the crucial role of AI in combating COVID-19, including diagnostic, epidemic spread prediction, patient characteristics, vaccine development, and supporting application development. Additionally, through comparing current COVID-19 datasets, the review highlights open research challenges for inspiring future AI applications in the pandemic.
Article
Computer Science, Artificial Intelligence
Zhi-Hui Zhan, Jian-Yu Li, Jun Zhang
Summary: Deep learning has achieved great success in solving learning problems, and evolutionary computation has been applied to optimize deep learning. Given the rapid development of evolutionary deep learning, it is necessary to review and summarize existing research to provide references for future studies and applications.
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)
Review
Computer Science, Information Systems
Donghong Han, Yanru Kong, Jiayi Han, Guoren Wang
Summary: This paper presents a detailed survey of music emotion recognition. It starts with some preliminary knowledge and introduces commonly used evaluation metrics. A three-part research framework is proposed, and the knowledge and algorithms involved in each part are analyzed in detail. The challenging problems and development trends of music emotion recognition technology are discussed, and the paper is summarized.
FRONTIERS OF COMPUTER SCIENCE
(2022)
Review
Chemistry, Analytical
Roberto Magherini, Elisa Mussi, Yary Volpe, Rocco Furferi, Francesco Buonamici, Michaela Servi
Summary: There is a growing interest in applying machine learning techniques to nephrology, providing physicians with additional tools for accurate and faster diagnoses, although the major limitation remains in creating public databases.
Article
Oncology
Sara E. Kochanny, Alexander T. Pearson
Summary: Academic cancer researchers and providers play crucial roles in guiding the successful translation of artificial intelligence applications into clinical cancer care practice. In academic settings, researchers and providers have access to key components such as algorithms, data, computational resources, and domain-specific expertise, which help drive progress in applied AI research and avoid common pitfalls.
Review
Chemistry, Medicinal
Julien Guiot, Akshayaa Vaidyanathan, Louis Deprez, Fadila Zerka, Denis Danthine, Anne-Noelle Frix, Philippe Lambin, Fabio Bottari, Nathan Tsoutzidis, Benjamin Miraglio, Sean Walsh, Wim Vos, Roland Hustinx, Marta Ferreira, Pierre Lovinfosse, Ralph T. H. Leijenaar
Summary: Radiomics is a method for quantitatively analyzing medical images to create diagnostic, prognostic, and/or predictive models. It utilizes sophisticated image analysis tools and statistical methods to extract hidden information in medical images, but caution is needed to avoid overenthusiastic claims and scientific pollution.
MEDICINAL RESEARCH REVIEWS
(2022)
Review
Biotechnology & Applied Microbiology
Yihao Liu, Minghua Wu
Summary: Deep learning has been successfully applied to various tasks in different fields, including disease diagnosis in medicine. By extracting multilevel features from medical data, deep learning helps doctors automatically assess diseases and monitor patients' physical health.
BIOENGINEERING & TRANSLATIONAL MEDICINE
(2023)
Review
Computer Science, Information Systems
Guillermo Iglesias, Edgar Talavera, Alberto Diaz-Alvarez
Summary: In recent years, deep learning has been revolutionized by the significant impact of Generative Adversarial Networks (GANs), which provide a unique architecture and generate incredible results. Due to the continuous development and wide range of applications, keeping up with the latest research in GANs becomes challenging. This survey aims to provide an overview of GANs, including the latest architectures, optimizations, validation metrics, and application areas, with the goal of guiding future researchers in achieving better results.
COMPUTER SCIENCE REVIEW
(2023)
Review
Oncology
Melissa Estevez, Corey M. Benedum, Chengsheng Jiang, Aaron B. Cohen, Sharang Phadke, Somnath Sarkar, Selen Bozkurt
Summary: This study presents an evaluation framework to assist model developers, data users, and other stakeholders in assessing the quality and applicability of data extracted using machine learning techniques from patient documents. This framework can facilitate effective utilization of this data in research.
Article
Gastroenterology & Hepatology
Danny Con, Daniel R. van Langenberg, Abhinav Vasudevan
Summary: This study compared the utility of deep learning with conventional algorithms in predicting response to anti-tumor necrosis factor (anti-TNF) therapy in Crohn's disease (CD) patients. The results showed that deep learning methods have the potential for stronger predictive performance compared to conventional model building methods in predicting remission after anti-TNF therapy in CD.
WORLD JOURNAL OF GASTROENTEROLOGY
(2021)
Review
Medicine, General & Internal
Md. Mohaimenul Islam, Tahmina Nasrin Poly, Belal Alsinglawi, Ming Chin Lin, Min-Huei Hsu, Yu-Chuan (Jack) Li
Summary: Artificial intelligence (AI) has shown significant potential in combating COVID-19 through the analysis of digital images, clinical data, and laboratory data. The study surveyed the use of AI for tasks such as detection, diagnosis, and drug repurposing related to COVID-19, highlighting both the achievements and challenges in this area. This paper provides a technical overview of AI models used in the fight against the COVID-19 pandemic, concluding with a brief discussion on the current state-of-the-art, limitations, and challenges.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Computer Science, Information Systems
Mohd Saad Hamid, NurulFajar Abd Manap, Rostam Affendi Hamzah, Ahmad Fauzan Kadmin
Summary: This article surveys the algorithm frameworks related to stereo matching algorithm, dividing them into traditional and artificial intelligence (AI) frameworks. AI-based methods show higher accuracy compared to traditional methods, ranking high in standard benchmark datasets. Recent trends in solving computer vision problems lean towards using AI and machine learning tools, with a focus on deep learning frameworks related to convolutional neural networks (CNN).
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Oncology
Vicente Guillem Porta, Carlos Camps, Miguel Angel Climent Duran, Enrique Gallardo, Aranzazu Gonzalez del Alba, Martin Lazaro-Quintela, Maria Jose Mendez Vidal, Alvaro Pinto Marin, Javier Puente, Cristina Anton-Rodriguez, Fernando Caballero-Martinez, Francisco J. Campos-Lucas, Ilse Lugo, Alvaro Rogado, Ignacio Duran
Summary: The study used the Delphi method to reach a consensus on 25 measures for evaluating quality of care in renal cancer. These measures cover all aspects and stages of renal cancer care.
CLINICAL & TRANSLATIONAL ONCOLOGY
(2022)
Article
Surgery
A. El-Hussuna, M. L. M. Karer, N. N. Uldall Nielsen, A. Mujukian, P. R. Fleshner, I. Iesalnieks, N. Horesh, U. Kopylov, H. Jacoby, H. M. Al-Qaisi, F. Colombo, G. M. Sampietro, M. V. Marino, M. Ellebaek, C. Steenholdt, N. Sorensen, V. Celentano, N. Ladwa, J. Warusavitarne, G. Pellino, A. Zeb, F. Di Candido, L. Hurtado-Pardo, M. Frasson, L. Kunovsky, A. Yalcinkaya, O. C. Tatar, S. Alonso, M. Pera, A. G. Granero, C. A. Rodriguez, A. Minaya, A. Spinelli, N. Qvist
Summary: In patients with active Crohn's disease, factors such as older age, residual abscess after PD, smoking, and low serum albumin concentration are associated with higher rates of postoperative complications. An interval of at least 2 weeks after successful PD is linked to reduced risk of abscess recurrence.
Article
Allergy
Silvia Sanchez-Garcia, Javier Ruiz-Hornillos, Marta Bernaola, Alicia Habernau-Mena, Eva Maria Lasa, Javier Contreras, Rocio Candon-Morillo, Cristina Anton-Rodriguez, Carmelo Escudero
Summary: This study aimed to analyze the effects of the SARS-CoV-2 pandemic on pediatric asthma control. The findings showed that pediatric asthma control improved during the pandemic, with a decrease in the need for controller medication and fewer visits to healthcare providers compared to the previous year.
ALLERGOLOGIA ET IMMUNOPATHOLOGIA
(2022)
Article
Health Care Sciences & Services
Maria Herrera Abian, Cristina Anton Rodriguez, Antonio Noguera
Summary: The study shows that the cost is significantly lower when patients receive care from a palliative care unit during their last hospital stay.
JOURNAL OF PAIN AND SYMPTOM MANAGEMENT
(2022)
Article
Immunology
Diana Tavares, Helena Mourino, Cristina Anton Rodriguez, Carlos Martin Saborido
Summary: This study evaluates the cost effectiveness of switching from trivalent inactivated vaccine (TIV) to quadrivalent inactivated vaccine (QIV) in the Portuguese elderly population from the perspective of the National Health Service. The findings indicate that QIV is not cost effective due to its high cost.
Article
Dermatology
Emilio Berna-Rico, Carlota Abbad-Jaime De Aragon, Angel Garcia-Aparicio, David Palacios-Martinez, Asuncion Ballester-Martinez, Jose-M Carrascosa, Pablo De La Cueva, Cristina Anton, Carlos Azcarraga-llobet, Emilio Garcia-Mouronte, Belen De Nicolas-Ruanes, Lluis Puig, Pedro Jaen, Nehal N. Mehta, Joel M. Gelfand, Alvaro Gonzalez-Cantero
Summary: Patients with psoriasis have a higher risk of cardiovascular events, but screening and treatment are not sufficient. Less than 30% of physicians perform comprehensive screening, and over 60% of primary care physicians are unaware of the association between psoriasis and cardiovascular disease. Among those who do not prescribe, 50% of dermatologists and rheumatologists would be willing to start prescribing statins.
ACTA DERMATO-VENEREOLOGICA
(2023)
Review
Medicine, General & Internal
Valle Coronado-Vazquez, Cristina Anton-Rodriguez, Juan Gomez-Salgado, Maria del Valle Ramirez-Duran, Santiago Alvarez-Montero
Summary: This study assessed the expected learning outcomes of medical humanities subjects in medical curriculum and connected these outcomes with the knowledge to be acquired in medical education. A meta-review of systematic and narrative reviews was conducted, revealing heterogeneity in the teaching of medical humanities in terms of both content and formal level. The learning outcomes of medical humanities include the acquisition of knowledge and skills to improve patient relationships, reduce burnout, and promote professionalism.
FRONTIERS IN MEDICINE
(2023)
Article
Medicine, General & Internal
Maria Herrera-Abian, Raul Castaneda-Vozmediano, Cristina Anton-Rodriguez, Domingo Palacios-Cena, Luz Maria Gonzalez-Morales, Bernadette Pfang, Antonio Noguera
Summary: Understanding patient and caregiver experience is crucial for person-centered care, especially in palliative care. This study aimed to compare the experiences of family caregivers in PCU and non-PCU units during their loved ones' last hospital admission. Differences were observed in terms of scientific appropriateness of care and person-centered care between the two groups.
ANNALS OF MEDICINE
(2023)
Review
Ophthalmology
Julio Gonzalez Martin-Moro, Jesus Zarallo-Gallardo, Elena Guzman-Almagro, Cristina Anton Rodriguez
Summary: There is great uncertainty about the usefulness of topical povidone iodine (PI) in the treatment of adenoviral conjunctivitis (AC). PI-DXM may have a small effect on AC duration. Future studies should standardize the reporting of results and include etiological confirmation and aspects relevant to patient quality of life.
CONTACT LENS & ANTERIOR EYE
(2023)
Article
Oncology
Juan Jesus Cruz Hernandez, Virginia Arrazubi Arrula, Yolanda Escobar Alvarez, Almudena Garcia Castano, Juan Jose Grau de Castro, Lara Iglesias Docampo, Julio Lambea Sorrosal, Pedro Perez Segura, Antonio Rueda Dominguez, Francisco J. Campos-Lucas, Irene Santamaria Rodriguez, Maria Bessa, Paula Gratal, Fernando Caballero-Martinez, Diana Monge Martin, Cristina Anton-Rodriguez, Rafael Lopez
Summary: This study aimed to develop a set of criteria and indicators to evaluate the quality of care for patients with head and neck cancer (HNC). Through a systematic literature review and a two-round Delphi method evaluation, a final set of 29 indicators were identified, covering diagnosis, treatment, follow-up, and health outcomes of HNC patients.
CLINICAL & TRANSLATIONAL ONCOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Alberto Nogales, Alvaro J. Garcia-Tejedor, Diana Monge, Juan Serrano Vara, Cristina Anton
Summary: Artificial intelligence, with deep learning being the most impactful technique, plays a significant role in the medical field where complex data and crucial decisions by doctors are involved. A systematic review conducted by a multidisciplinary team identified the increasing number of publications on deep learning in medicine, with convolutional neural networks being the most commonly used models, especially in oncology for image analysis.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2021)
Article
Nutrition & Dietetics
Alberto Villaverde-Nunez, Cristina Perez Ramos, Maria Victoria Sanz Lobo, Maria Del Carmen Morgado Benito, Virginia Martinez-Ibanez, Noelia Avecilla Nieto, Cristina Anton Rodriguez
Summary: The study revealed that nearly half of patients admitted to the hospital were malnourished, with the prevalence increasing to almost two-thirds after a week of hospitalization. Malnutrition was associated with longer hospital stay, older age, weight loss, medical specialty, and readmissions.
NUTRICION HOSPITALARIA
(2021)
Meeting Abstract
Oncology
Vicente Guillem, Javier Puente, Carlos Camps, Miguel Angel Climent Duran, Enrique Gallardo Diaz, Aranzazu Gonzalez del Alba, Martin Emilio Lazaro Quintela, Maria Jose Mendez Vidal, Cristina Anton, Fernando Caballero, Francisco J. Campos, Ilse Lugo, Diana Monge, Alvaro Rogado, Irene Santamaria Rodriguez, Alvaro Pinto, Ignacio Duran
JOURNAL OF CLINICAL ONCOLOGY
(2020)
Article
Medicine, General & Internal
Jaime Monserrat Villatoro, Irene Garcia Garcia, David Bueno, Rafael de la Camara, Miriam Estebanez, Ana Lopez de la Guia, Francisco Abad-Santos, Cristina Anton, Gina Mejia, Maria Jose Otero, Elena Ramirez Garcia, Jesus Frias Iniesta, Antonio Carcas, Alberto M. Borobia
Article
Computer Science, Artificial Intelligence
Qianghua Liu, Yu Tian, Tianshu Zhou, Kewei Lyu, Ran Xin, Yong Shang, Ying Liu, Jingjing Ren, Jingsong Li
Summary: This study proposes a few-shot disease diagnosis decision making model based on a model-agnostic meta-learning algorithm (FSDD-MAML). It significantly improves the diagnostic process in primary health care and helps general practitioners diagnose few-shot diseases more accurately.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)
Article
Computer Science, Artificial Intelligence
Balazs Borsos, Corinne G. Allaart, Aart van Halteren
Summary: The study demonstrates the feasibility of predicting functional outcomes for ischemic stroke patients and the usability of multimodal deep learning architectures for this purpose.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)
Article
Computer Science, Artificial Intelligence
Abdelmoniem Helmy, Radwa Nassar, Nagy Ramdan
Summary: This study utilizes machine learning models to detect depression symptoms in Arabic and English texts, and provides manually and automatically annotated tweet corpora. The study also develops an application that can detect tweets with depression symptoms and predict depression trends.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)