promor: a comprehensive R package for label-free proteomics data analysis and predictive modeling.

Summary: We present promor, a comprehensive, user-friendly R package that streamlines label-free quantification proteomics data analysis and building machine learning-based predictive models with top protein candidates. Availability and implementation: promor is freely available as an open source R package on the Comprehensive R Archive Network (CRAN) (https://CRAN.R-project.org/package=promor) and distributed under the Lesser General Public License (version 2.1 or later). Development version of promor is maintained on GitHub (https://github.com/caranathunge/promor) and additional documentation and tutorials are provided on the package website (https://caranathunge.github.io/promor/). Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Reimagining Medical Education in the Age of AI.

Available medical knowledge exceeds the organizing capacity of the human mind, yet medical education remains based on information acquisition and application. Complicating this information overload crisis among learners is the fact that physicians' skill sets now must include collaborating with and managing artificial intelligence (AI) applications that aggregate big data, generate diagnostic and treatment recommendations, and assign confidence ratings to those recommendations. Thus, an overhaul of medical school curricula is due and should focus on knowledge management (rather than information acquisition), effective use of AI, improved communication, and empathy cultivation.

Emerging Roles of Virtual Patients in the Age of AI.

Today's web-enabled and virtual approach to medical education is different from the 20th century's Flexner-dominated approach. Now, lectures get less emphasis and more emphasis is placed on learning via early clinical exposure, standardized patients, and other simulations. This article reviews literature on virtual patients (VPs) and their underlying virtual reality technology, examines VPs' potential through the example of psychiatric intake teaching, and identifies promises and perils posed by VP use in medical education.

Medical Education Must Move From the Information Age to the Age of Artificial Intelligence.

Noteworthy changes coming to the practice of medicine require significant medical education reforms. While proposals for such reforms abound, they are insufficient because they do not adequately address the most fundamental change-the practice of medicine is rapidly transitioning from the information age to the age of artificial intelligence. Increasingly, future medical practice will be characterized by: the delivery of care wherever the patient happens to be; the provision of care by newly constituted health care teams; the use of a growing array of data from multiple sources and artificial intelligence applications; and the skillful management of the interface between medicine and machines. To be effective in this environment, physicians must work at the top of their license, have knowledge spanning the health professions and care continuum, effectively leverage data platforms, focus on analyzing outcomes and improving performance, and communicate the meaning of the probabilities generated by massive amounts of data to patients, given their unique human complexities. The authors believe that a "reboot" of medical education is required that makes better use of the findings of cognitive psychology and pays more attention to the alignment of humans and machines in education and practice. Medical education needs to move beyond the foundational biomedical and clinical sciences. Systematic curricular attention must focus on the organization of professional effort among health professionals, the use of intelligence tools involving large data sets, and machine learning and robots, all the while assuring the mastery of compassionate care.

The evolution of medical simulators.

Medical simulators continue to evolve, developing capabilities that make their use in medical and health professions education more likely. Among these capabilities are: wireless communication, portability, compactness, and user-friendliness. Demands for effective team training and decision support will drive the next generation of medical simulators.

Visualizing the medical modeling and simulation database: trends in the research literature.

Medical modeling and simulation literature has undergone significant changes from 2000 until 2007. The MMVR Conference and the MMSD provide two avenues for observing trends in medical modeling and simulation literature. The literature submitted to MMVR and MMSD from 2000 to 2007 were placed into 8 categories and assessed through meta-analysis.

Simulating the domain of medical modeling and simulation: the medical modeling and simulation database.

Over the past year the National Center for Collaboration in Medical Modeling and Simulation's (NCCMMS) Medical Modeling and Simulation Database (MMSD) has grown dramatically. There are now over 170,000 entries including current articles and upcoming conference listings. In addition, in the near future, the scope of the NCCMMS website will expand to include an evaluation section where NCCMMS researchers will compile data describing the efficacy and cost efficiency of many commercially available simulators. The NCCMMS also plans to create a new collaborative forum on the website. This message board area will provide a single location for researchers to discuss new simulation techniques and programs. It will help to facilitate communication between companies and researchers in the field by creating a comprehensive forum for medical modeling and simulation discussions. The newly expanded MMSD and NCCMMS websites are designed to create a simple way for researchers and companies to work together to facilitate the sharing of information and to spur advancement of the medical modeling and simulation discipline.

Tracking the domain: the medical modeling and simulation database.

To foster awareness of the magnitude and breadth of activity and to foster collaboration among the participants, the National Center for Collaboration in Medical Modeling and Simulation (NCCMMS) has created the Medical Modeling and Simulation Database (MMSD). The MMSD consists of two web-based, searchable compilations: one, the Research Database, that contains bibliographic information on published articles and abstracts (where available) and a second, the Companies and Projects Database, that maintains contact information for research centers, development and application programs, journals and conferences. NCCMMS is developing the MMSD to increase awareness of the breadth of the medical modeling domain and to provide a means of fostering collaboration and bringing like-minded organizations and researchers into more frequent contact with each other, thus speeding advancement of medical modeling and simulation.

Analyzing the MMVR research space: past emphases, future directions.

The MMVR Conference is one of a handful of national forums where leading researchers regularly convene to discuss medical modeling and simulation. As such, the presentations made during the conference represent a reasonable overview of both the state-of-the-art in virtual reality in medicine and the basic and applied research trends in the field. This article describes those trends and some of the implications based on a meta-analysis of almost three hundred articles published as a result of the MMVR Conferences in 2000, 2001, and 2002.