MMKP: A mind mapping knowledgebase prototyping tool for precision medicine

Abstract

BackgroundWith significant advancements in the area of precision medicine, the breadth and complexity of the relevant knowledge in the field has increased significantly. However, the difficulty associated with dynamic modelling and the disorganization of such knowledge hinders its rapid development potential.ResultsTo overcome the difficulty in using the relational database model for dynamic modelling, and to aid in the organization of precision medicine knowledge, we developed the Mind Mapping Knowledgebase Prototyping (MMKP) tool. The MMKP implements a novel design that we call a “polymorphic foreign key”, which allows the establishment of a logical linkage between a single table field and a record from any table. This design has advantages in supporting dynamic changes to the structural relationships in precision medicine knowledge. Knowledge stored in MMKP is presented as a mind map to facilitate human interaction. When using this tool, medical experts may curate the structure and content of the precision knowledge in a flow that is similar to the human thinking process.ConclusionsThe design of polymorphic foreign keys natively supports knowledge modelling in the form of mind mapping, which avoids the hard-coding of medical logic into a rigid database schema and significantly reduces the workload that is required for adapting a relational data model to future changes to the medical logic. The MMKP tool provides a graphical user interface for both data management and knowledgebase prototyping. It supports the flexible customization of the data field constraints and annotations. MMKP is available as open-source code on GitHub: https://github.com/ZjuLiangsl/mmkp.

Advancing precision medicine in medical education: Integrated, precise and data‐driven smart solutions

“…In addition, as mentioned by Arnall et al [71] clinical pharmacists should integrate Precision Medicine Programs and Systems as part of oncology training and cancer care. Moving from Personalized to Precision Cancer Medicine will require the merging of the genome and transcriptome sequencing and editing technologies if we are to advance the prevention, diagnosis, and treatment of cancers [72–74].…”

“…At the same time the benefits of Precision/Personalized Medicine and the major obstacles for all stakeholders involved are summarized as well as specific solutions are provided. Knowledge and perception of Medical and Pharmacy students towards Pharmacogenomics and Genetics is also presented [6, 8–10, 22, 27–29, 33, 34, 45, 51, 53–55, 59, 67, 74–77, 81–83, 85–107, 112, 113, 121].…”

Modified Artificial Bee Colony Algorithm for Multiple-Choice Multidimensional Knapsack Problem

“…A feasible candidate solution with relatively low nectar content may yield a better global solution than another candidate solution with higher nectar content. Therefore, the greedy selection between the current solution Xl and the new solution Vl is based on the highest fitness value computed by ( 14) instead of (9).…”

“…The MMKP is a generalization of the classical knapsack problem (KP) [1]. It is significant because it can model a wide range of real-time applications such as resource allocation [2], intelligent transportation systems [3], logistics [4], quality of service (QoS) [5], [6], web service composition [7], Energy-Efficient Offloading in Mobile Edge Computing [8], medicine [9], budgeting problems [10], hardware design [11], and cloud computing [12]. Formally, the MMKP can be expressed as a set of items divided into n disjoint groups and an m-dimensional resource constraint represented by the vector of resource availability 𝑏 𝑘 = {𝑏 1 , … , 𝑏 𝑚 }.…”