Titles | Informations | Keywords | Papers | Source |
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Deep Learning for Medical Image Analysis and Medical Natural Language Processing | Dear Colleagues, This Special Issue mainly focuses on the application of deep learning to medical image analysis and medical natural language processing. We welcome original papers and review papers related to the topics below. In particular, this Special Issue welcomes the papers where both medical image analysis and medical natural language processing are used as multi-modal deep learning. Research Topics: Dr. Mizuho NishioDr. Koji FujimotoTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | deep learning medical image analysis natural language process medical imaging cancer | 11 | 光热生物数据库 |
Advances in Genetics and Precision Medicine in Human Diseases | Dear Colleagues, Precision medicine is an emerging approach for disease treatment using genetics and genomics information. The majority of genetic variants are probably functionally neutral and can exert variant-specific effects on the regulation of gene expression. Such genetic variants are vital because they can be used as biomarkers that indicate the prognosis of potentially malignant and malignant lesions and may thus be involved in early intervention and diagnosis in patients at high risk. We are pleased to invite you to our Special Issue “Advances in Genetics and Precision Medicine in Human Diseases”. We look forward to receiving your contributions. Prof. Dr. Shun-Fa YangDr. Shih-Chi SuTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | genetics polymorphism gene variant genome-wide association studies precision medicine pharmacogenetics mutation epigenetics cancer biomarkers single nucleotide polymorphism | 56 | 光热生物数据库 |
Real-Time Monitoring for Improving Cancer Diagnosis and Prognosis | Dear Colleagues, For deadly cancers, which are difficult to successfully treat after tumor metastasis, identification of useful prognostic and predictive biomarkers for informing clinicians early during treatment of the need to revise treatments for patients is expected to improve treatment outcomes. Real- time monitoring of cancers during treatment will allow early detection of minimal residual disease and the presence of tumor heterogeneity, which need to be addressed for successful long-term treatment success. Liquid biopsies allow non-invasive serial timepoint assessment of a patient’s treatment status. Detection of circulating tumor DNA and circulating tumor cells are now reported for different cancers that herald their usefulness in cancer screening and treatment decisions. Detection of key drug-targetable mutations early during the progression of the cancer can provide better alternatives for patient treatment. This Special Issue highlights recent approaches for addressing improving patient outcomes via real-time monitoring of cancer patients during therapy to identify earlier timepoints for clinical decisions on long-term treatment. Prof. Dr. Maria Li LungDr. Josephine KoTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | cancer biomarkers liquid biopsies ctDNA circulating tumor cell real-time monitoring | 16 | 光热生物数据库 |
Rheumatic Disorder: From Basic Science to Clinical Practice | Dear Colleagues, Autoimmune rheumatic diseases (RDs) are chronic inflammatory diseases with a major health impact worldwide, but their management and classification are sometimes difficult due to unknown aetiology and heterogeneity in their clinical presentation. RDs have the largest and consistent impact across all ages of the population, and they affect a significant proportion of the population. Their economic and social burden results from a decreased quality of life, lost productivity, and increased costs of health care. Moreover, although RDs affect people of all ages, the demographic structure of the population indicates an increasing tendency towards an older population along with an increasing prevalence of these diseases. Therefore, improving our knowledge of RDs, from basic science to clinical practice, has become critical. The heterogeneity of RDs and the lack of any clear clinical correlation with pathology makes for inexact estimation of their incidence and prevalence. Moreover, more investigation is needed concerning the causes and mechanisms affecting the development and progression of these disorders, and moreover more studies are needed to discover innovative treatments. As a result, challenges in studying RDs lie in achieving accurate epidemiological data and making efforts to obtain significant progress in terms of etiological mechanisms, clinical behaviour and the genetic/epigenetic basis of the diseases, as well as early diagnosis, treatment, and management of patients. Dr. Giulia CassoneDr. Caterina VacchiDr. Andreina ManfrediTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | rheumatic diseases etiology epidemiology therapy diagnosis classification risk factors | 10 | 光热生物数据库 |
Metabolic Syndrome, Biomarkers and Lifestyles | Dear Colleagues, Metabolic syndrome is a condition characterized by a combination of risk factors that increases the likelihood of developing cardiovascular disease, stroke, and type 2 diabetes. The prevalence of metabolic syndrome has steadily increased in recent years and is estimated to affect approximately one quarter of the world's population. Various markers of metabolic syndrome have been recognized and are still being studied. Based on the pathophysiology of visceral adipose tissue, adipocyte dysfunction, chronic low-grade inflammation, and insulin resistance, biomarkers such as anthropometric markers, insulin resistance markers, inflammatory markers, various adipokines, oxidative stress markers, vascular markers, lipoprotein markers, and hormonal markers have been proposed and play an important role in the diagnosis and monitoring of metabolic syndrome. Lifestyle factors such as diet and physical activity are key to managing metabolic syndrome. A healthy diet can help reduce the risk of developing metabolic syndrome and improve biomarker levels. Regular exercise can also be effective in reducing the risk of metabolic syndrome by promoting weight loss, improving insulin sensitivity, and lowering blood pressure. As such, metabolic syndrome is an important public health issue due to its association with several chronic diseases. Biomarkers can help diagnose and manage metabolic syndrome, and lifestyle interventions such as diet and exercise can effectively reduce risk and improve biomarker levels. Education on and awareness of the importance of making healthy lifestyle choices is also important. This topic aims to cover all these aspects. Prof. Dr. Sang Yeoup LeeProf. Dr. Young Hye ChoTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | metabolic syndrome biomarker lifestyle diet exercise obesity lipid insulin resistance diabetes hypertension | 23 | 光热生物数据库 |
AI in Medical Imaging and Image Processing | Dear Colleagues, In modern healthcare, the importance of computer-aided diagnosis is quickly becoming obvious, with clear benefits for the medical professionals and patients. Automatization of processes traditionally maintained by human professionals is also growing in importance. The process of image analysis can be supported by the use of networks that can carry out multilayer analyses of patterns—collectively called artificial intelligence (AI). If supported by large datasets of input data, computer networks can suggest the result with low error bias. Medical imaging focused on pattern detection is typically supported by AI algorithms. AI can be used as an important aid in three major steps of decision making in the medical imaging workflow: detection (image segmentation), recognition (assignment to the class), and result description (transformation of the result to natural language). The implementation of AI algorithms may participate in the diagnostic process standardization and markedly reduces the time needed to achieve pathology detection and description of the results. With AI support, medical specialists may work more effectively, which can improve healthcare quality. As AI has been a topic of interest for a while now, there are many approaches to and techniques for the implementation of AI based on different computing methods designed to work in various systems. The aim of this Special Issue in to present the current knowledge dedicated to the AI methods used in medical systems, with their applications in different fields of diagnostic imaging. Our goal is for this collection of works to contribute to the exchange of knowledge resulting in a better understanding of AI technical aspects and applications in modern radiology. Dr. Karolina NurzynskaProf. Dr. Michał StrzeleckiProf. Dr. Adam PiorkowskiDr. Rafał ObuchowiczTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | artificial intelligence computer-aided diagnosis medical imaging image analysis image processing | 41 | 光热生物数据库 |
From Basic Research to a Clinical Perspective in Oncology | Dear Colleagues, We are happy to open this Topic in cooperation with the OncoHub Conference and share the aim of creating a proper space where interdisciplinary teams of biomedical researchers could share their latest scientific advances and bring together the cancer research medical communities to inspire innovation and build knowledge, networks, and collaborations. Our main focus is on bridging the gap between clinical research, clinicians, and industry by identifying promising tools for drug discovery and targets for novel therapies. For this, we encourage the submission of any original work or review manuscript that could inspire other professionals to gain insight into the clinical relevance of molecular diagnostic advances, circulating markers for liquid biopsy development, disease modeling in bioprinted microfluidic devices, modern endoscopic and/or surgical techniques in different cancer types, etc. Dr. Bianca GǎlǎţeanuDr. Octav GinghinăDr. Ariana HuditaTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | liquid biopsy tumor microenvironment immuno-oncology sentinel lymph node mapping radiofrequency ablation | 7 | 光热生物数据库 |
Advances in Musculoskeletal Imaging and Their Applications, 2nd Edition | Dear Colleagues, Radiographic acquisition techniques have undergone tremendous improvements since their invention. Image resolution has greatly increased and the reduction in the dose of X-ray radiation required for its creation has been achieved. The increased amount of imaging data does not necessarily mean that more medical information is accessible to the reader. Some (but often important) information is hidden from the radiologist. This is especially true for radiographic techniques. The purpose of advanced image-analysis systems is to extract occulted data to improve the objectivity of diagnosis for a given case. The treatment of clinical problems with information obtained using advanced image analyses has increased. In musculoskeletal radiology, proven associations exist between bone scan analyses, patient health and metabolic status. Moreover, the processes of bone maturation, bone healing, bone demineralization and deformation due to overuse can be extensively analyzed with the use of CR, CT and MRI. Advanced methods significantly improve differentiation and hence the diagnostic process of medication for different lesions including neoplasms of the bone. Papers investigating the application of both classical image processing and artificial intelligence (AI) methods in the analysis and extraction of diagnostically useful data from medical images are welcomed in this Special Issue. Such methods assist in the investigation of the shape and geometry of, for example, bone tissue or its fragments. Other AI approaches allow for the automatic detection and segmentation of tissues or organs and the assessment of their pathologies. For this purpose, the achievements of radiomics are particularly useful, including image-texture analyses. Various machine learning methods are also useful for exploring medical imaging data and are widely used in medical diagnostic support systems. Deep learning algorithms play a particularly important role in this respect. Recently, dynamic developments have been achieved in the field of deep learning algorithms, and their effectiveness has been confirmed in numerous applications of medical image analyses of various modalities. Prof. Dr. Rafał ObuchowiczDr. Monika OstrogórskaProf. Dr. Michał StrzeleckiProf. Dr. Adam PiórkowskiTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | bone imaging musculoskeletal imaging image processing image analysis segmentation textural analysis machine learning | 5 | 光热生物数据库 |
Applications of Immunohistochemical Staining in Brain Diseases | Dear Colleagues, Immunohistochemical staining (IHC) can be used to qualitatively or quantitatively recognize analytes involving peptides, proteins, or small molecules. The IHC technique can link to molecular imaging, bioinformatics analysis, artificial intelligence (AI)-based methods, therapeutic targeting with brain therapy, and basic research in brain diseases. Advances in IHC-related applications enable early detection and precise treatment in disease management. This Topic aims to apply cutting-edge research into multidisciplinary frontier viewpoints to various novelty concerns and provide insights into clinical issues underlying recent advances in aspects of disease treatment. Authors are invited to submit both reviews and original articles to our Topic collection. Potential subject include, but are not limited to: Prof. Dr. Andrew Chih Wei HuangDr. Bai Chuang ShyuProf. Dr. Seong Soo A. AnDr. Anna KozłowskaTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | 2 | 光热生物数据库 | |
New Advances in Musculoskeletal Disorders | Dear Colleagues, Musculoskeletal disorders (MSDs) are the leading contributor to disability worldwide, with lower back pain being the single leading cause of disability across 160 countries. Disability associated with MSDs has been increasing, and it is projected to rapidly increase in the coming decades due to population increase and aging. MSDs are considered work-related musculoskeletal disorders (WMSDs) if an event or exposure in the work environment either caused or contributed to the resulting disorders or significantly aggravated a pre-existing disorder. In the USA, 272,780 WMSD cases were reported in 2018, with the incidence rate of 27.2 per 10,000 full-time workers, accounting for approximately 30% of all occupational injuries and illnesses involving days away from work. Therefore, it is crucial to survey the prevalence and risk factors of WMSDs and to develop preventive measures to reduce WMSDs. This Topic focuses on updating our knowledge concerning WMSDs. New research papers, reviews, case studies and any WMSDs relevant studies are also welcome to this Topic. The major themes of which are as follows: Prof. Dr. Dohyung KeeProf. Dr. Inseok LeeTopic Editors MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication: | musculoskeletal disorders work-related musculoskeletal disorders musculoskeletal disorder risk factors musculoskeletal load posture classification scheme observational techniques postural load | 10 | 光热生物数据库 |