الصفحة 1
الصفحة 1
Intelligent drugs : How AI is transforming healthcare
The progress of biotechnologies and artificial intelligence allowed the development of vaccines in less than a year, thus saving millions of human lives and preserving the global economy. The emergence of intelligent drugs is highlighted, with the promise of ultra-targeted, more effective, and safer treatments against a wide range of diseases. Personalized medicine then becomes realistic, with computer-designed drugs, perfectly adapted to each individual, tested on virtual patients before their real use. In the near future, thanks to AI, new drugs will improve physical performance, stimulate cognitive abilities, prevent diseases, and slow down aging.
Innovations in healthcare and outcome measurement : New approaches for a healthy lifestyle
Aims to bring up-to-date new ideas, opinions, development, and critical issues in healthcare and personalized medicine. We are interested in relevant articles covering a broad range of topics, such as: Advances in medical devices, Digitalization and data-driven technologies, AI and algorithm-based drug development (molecule building, enhancement, clinical trials), Diagnostic imaging, Personalized medicine, Nutrition, Oral health care, Healthcare management in certain diseases and population groups, Regulatory developments, Data management, Digital healthcare.
High performance computing for drug discovery and biomedicine
Explores the application of high-performance computing (HPC) technologies to computational drug discovery (CDD) and biomedicine. Collects CDD approaches that, together with HPC, can revolutionize and automate drug discovery process, such as knowledge graphs, natural language processing (NLP), Bayesian optimization, automated virtual screening platforms, alchemical free energy workflows, fragment-molecular orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC), and the potential of cloud computing for drug discovery. And delves into computational algorithms and workflows for biomedicine, featuring an HPC framework to assess drug-induced arrhythmic risk, digital patient applications relevant to the clinic, virtual human simulations, cellular and whole-body blood flow modeling for stroke treatments, prediction of the femoral bone strength from CT data, and many more subjects.
Fundamentals of Clinical Data Science
This book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare.
Emerging Technologies in Oral and Maxillofacial Surgery
Covers the application of emerging technologies, occurring after the 4th industrial revolution, in oral and maxillofacial surgery (OMFS) and introduces a new era of personalized medicine in this discipline. It describes the manufacturing and data acquisition methods, in detail, including the advantages and disadvantages of each process. The workflow of using the emerging technologies in reconstructive treatments, orthognathic surgery, implant dentistry, robotic surgery and bio‑fabrication have been covered in separate chapters.
Data Integration in the Life Sciences ; Vol. 4075 ; 3rd International Workshop, DILS 2006, Hinxton, UK, July 20-22, 2006, Proceedings
Data management and data integration are fundamental problems in the life sciences. Advances in molecular biology and molecular medicine are almost u- versallyunderpinned by enormouse?orts in data management,data integration, automatic data quality assurance, and computational data analysis. Many hot topics in the life sciences, such as systems biology, personalized medicine, and pharmacogenomics, critically depend on integrating data sets and applications producedby di?erent experimentalmethods, in di?erent researchgroups,andat di?erent levels of granularity.
Critical issues in head and neck oncology : Key concepts from the eighth THNO meeting
Reviews the state-of-the-art knowledge with emphasis on multidisciplinary decision and management of head and neck cancer. The book provides significant detail on a wide range of topics including: the role of new targets for treatment, immunotherapy, resistance mechanisms, standardizing molecular profiling programs, and new methods to guide therapeutic approaches.
Clinical metabolomics applications in genetic diseases
Helps readers discover the forefront of personalized medicine on clinical metabolomics and its applications in genetic diseases. This comprehensive guide offers a functional relationship map between cell components and genetic variations in various diseases, providing insights that can be applied to personalized medicine. Covers the latest developments in metabolomics for health, with practical guidance for clinical experts looking to advance their laboratory techniques and career. The metabolomics profile is a powerful tool that has revolutionized our understanding of the relationship between genetics, clinical readouts, and disease outcomes. By integrating metabolomics with genomics and clinical phenotypes, the authors have developed diagnostic and prediction models that have vastly improved patient outcomes and deepened the understanding of disease mechanisms.
Biomarkers in drug discovery and development : A handbook of practice, application, and strategy
Discusses biomarker characterization and validation and applications throughout drug discovery and development. Explains where proper use of biomarkers can substantively impact drug development timelines and costs, enable selection of better compounds and reduce late stage attrition, and facilitate personalized medicine. Helps readers get a better understanding of biomarkers and how to use them, for example which are accepted by regulators and which still non-validated and exploratory. Updates developments in genomic sequencing, and application of large data sets into pre-clinical and clinical testing; and adds new material on data mining, economics, and decision making, personal genetic tools, and wearable monitoring. Includes case studies of biomarkers that have helped and hindered decision making
Autoimmunity : Methods and protocols
Brings together a comprehensive and up-to-date collection of protocols that reflect the diverse experimental strategies. Chapters detail T-cell, macrophage characterization, neutrophil functional assays, organoid culture methods, spatial transcriptomics, RNA FISH, microRNA profiling, and ribosome profiling. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.
Artificial intelligence based cancer nanomedicine : Diagnostics, therapeutics and bioethics
Nanomedicine is evolving with novel drug formulations devised for multifunctional approaches towards diagnostics ad therapeutics. Nanomedicine-based drug therapy is normally explored at a fixed dose. The drug action is time-dependent, dose-dependent and patient-specific. To overcome challenges of nanomedicine testing, artificial intelligence (AI) serves as a helping tool for optimizing the drug and dose parameters. Real time conversions between these two features enables upgradation of patient data acquisition and improved design of nanomaterials. In this scenario, AI-based pattern analysis and algorithms models can greatly improve accuracy of diagnostics and therapeutics.
