Precision Medicine, Data-Driven Diagnosis and Treatment

2017 ◽  
pp. 15-34
Author(s):  
Harry Glorikian ◽  
Malorye Allison Branca
Keyword(s):  
Precision Medicine ◽  
Data Driven ◽  
Diagnosis And Treatment

Cancer Biomarker Discovery for Precision Medicine: New Progress

2020 ◽  
Vol 26 (42) ◽  
pp. 7655-7671 ◽  
Author(s):  
Jinfeng Zou ◽  
Edwin Wang
Keyword(s):  
Precision Medicine ◽  
Cancer Patients ◽  
Clinical Application ◽  
Liquid Biopsy ◽  
Biomarker Discovery ◽  
Deep Understanding ◽  
Genetic Mutation ◽  
Data Driven ◽  
Novel Approaches ◽  
Functional Biomarkers

Background: Precision medicine puts forward customized healthcare for cancer patients. An important way to accomplish this task is to stratify patients into those who may respond to a treatment and those who may not. For this purpose, diagnostic and prognostic biomarkers have been pursued. Objective: This review focuses on novel approaches and concepts of exploring biomarker discovery under the circumstances that technologies are developed, and data are accumulated for precision medicine. Results: The traditional mechanism-driven functional biomarkers have the advantage of actionable insights, while data-driven computational biomarkers can fulfill more needs, especially with tremendous data on the molecules of different layers (e.g. genetic mutation, mRNA, protein etc.) which are accumulated based on a plenty of technologies. Besides, the technology-driven liquid biopsy biomarker is very promising to improve patients’ survival. The developments of biomarker discovery on these aspects are promoting the understanding of cancer, helping the stratification of patients and improving patients’ survival. Conclusion: Current developments on mechanisms-, data- and technology-driven biomarker discovery are achieving the aim of precision medicine and promoting the clinical application of biomarkers. Meanwhile, the complexity of cancer requires more effective biomarkers, which could be accomplished by a comprehensive integration of multiple types of biomarkers together with a deep understanding of cancer.

Diagnosis and Treatment of Breast Cancer in the Precision Medicine Era

2020 ◽  
pp. 53-61 ◽  
Author(s):  
Jing Yan ◽  
Zhuan Liu ◽  
Shengfang Du ◽  
Jing Li ◽  
Li Ma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Precision Medicine ◽  
Diagnosis And Treatment

scholarly journals Precision Medicine

2019 ◽  
Vol 6 (1) ◽  
pp. 263-286 ◽  
Author(s):  
Michael R. Kosorok ◽  
Eric B. Laber
Keyword(s):  
Health Care ◽  
Precision Medicine ◽  
Decision Rules ◽  
Data Driven ◽  
Care Process ◽  
Treatment Regimes ◽  
Specific Diet ◽  
Recommended Action ◽  
Selection Of

Precision medicine seeks to maximize the quality of health care by individualizing the health-care process to the uniquely evolving health status of each patient. This endeavor spans a broad range of scientific areas including drug discovery, genetics/genomics, health communication, and causal inference, all in support of evidence-based, i.e., data-driven, decision making. Precision medicine is formalized as a treatment regime that comprises a sequence of decision rules, one per decision point, which map up-to-date patient information to a recommended action. The potential actions could be the selection of which drug to use, the selection of dose, the timing of administration, the recommendation of a specific diet or exercise, or other aspects of treatment or care. Statistics research in precision medicine is broadly focused on methodological development for estimation of and inference for treatment regimes that maximize some cumulative clinical outcome. In this review, we provide an overview of this vibrant area of research and present important and emerging challenges.

scholarly journals Diagnosis and treatment of cholangiocarcinoma in era of precision medicine

2017 ◽  
Vol 25 (24) ◽  
pp. 2167
Author(s):  
Yan Sun ◽  
Bao-Rong Chi
Keyword(s):  
Precision Medicine ◽  
Diagnosis And Treatment

scholarly journals Precision Neurosurgery: A Path Forward

2021 ◽  
Vol 11 (10) ◽  
pp. 1019
Author(s):  
Vianney Gilard ◽  
Stéphane Derrey ◽  
Stéphane Marret ◽  
Soumeya Bekri ◽  
Abdellah Tebani
Keyword(s):  
Precision Medicine ◽  
Data Analytics ◽  
Historical Perspective ◽  
Molecular Profiling ◽  
Data Driven ◽  
Medical Community ◽  
Technological Advances ◽  
Conceptual Shift ◽  
The Impact ◽  
Patient Centric

Since the inception of their profession, neurosurgeons have defined themselves as physicians with a surgical practice. Throughout time, neurosurgery has always taken advantage of technological advances to provide better and safer care for patients. In the ongoing precision medicine surge that drives patient-centric healthcare, neurosurgery strives to effectively embrace the era of data-driven medicine. Neuro-oncology best illustrates this convergence between surgery and precision medicine with the advent of molecular profiling, imaging and data analytics. This convenient convergence paves the way for new preventive, diagnostic, prognostic and targeted therapeutic perspectives. The prominent advances in healthcare and big data forcefully challenge the medical community to deeply rethink current and future medical practice. This work provides a historical perspective on neurosurgery. It also discusses the impact of the conceptual shift of precision medicine on neurosurgery through the lens of neuro-oncology.

scholarly journals A quantum-enhanced precision medicine application to support data-driven clinical decisions for the personalized treatment of advanced knee osteoarthritis: development and preliminary validation of precisionKNEE QNN

2021 ◽  
Author(s):  
Stefano Olgiati ◽  
Nima Heidari ◽  
Davide Meloni ◽  
Federico Pirovano ◽  
Ali Noorani ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computational Complexity ◽  
Knee Osteoarthritis ◽  
Precision Medicine ◽  
Real World ◽  
Data Driven ◽  
Personalized Treatment ◽  
Validation Dataset ◽  
Clinical Decisions ◽  
Quantum Machine Learning

Background Quantum computing (QC) and quantum machine learning (QML) are promising experimental technologies which can improve precision medicine applications by reducing the computational complexity of algorithms driven by big, unstructured, real-world data. The clinical problem of knee osteoarthritis is that, although some novel therapies are safe and effective, the response is variable, and defining the characteristics of an individual who will respond remains a challenge. In this paper we tested a quantum neural network (QNN) application to support precision data-driven clinical decisions to select personalized treatments for advanced knee osteoarthritis. Methods Following patients consent and Research Ethics Committee approval, we collected clinico-demographic data before and after the treatment from 170 patients eligible for knee arthroplasty (Kellgren-Lawrence grade ≥ 3, OKS ≤ 27, Age ≥ 64 and idiopathic aetiology of arthritis) treated over a 2 year period with a single injection of microfragmented fat. Gender classes were balanced (76 M, 94 F) to mitigate gender bias. A patient with an improvement ≥ 7 OKS has been considered a Responder. We trained our QNN Classifier on a randomly selected training subset of 113 patients to classify responders from non-responders (73 R, 40 NR) in pain and function at 1 year. Outliers were hidden from the training dataset but not from the validation set. Results We tested our QNN Classifier on a randomly selected test subset of 57 patients (34 R, 23 NR) including outliers. The No Information Rate was equal to 0.59. Our application correctly classified 28 Responders out of 34 and 6 non-Responders out of 23 (Sensitivity = 0.82, Specificity = 0.26, F1 Statistic= 0.71). The Positive (LR+) and Negative (LR-) Likelihood Ratios were respectively 1.11 and 0.68. The Diagnostic Odds Ratio (DOR) was equal to 2. Conclusions Preliminary results on a small validation dataset show that quantum machine learning applied to data-driven clinical decisions for the personalized treatment of advanced knee osteoarthritis is a promising technology to reduce computational complexity and improve prognostic performance. Our results need further research validation with larger, real-world unstructured datasets, and clinical validation with an AI Clinical Trial to test model efficacy, safety, clinical significance and relevance at a public health level.

Diagnosis and treatment in the era of precision medicine – Precision medicine and tailor-made medicine

2017 ◽  
Vol 6 ◽  
pp. 1-3 ◽  
Author(s):  
Masayoshi Nagata ◽  
Shigeo Horie
Keyword(s):  
Precision Medicine ◽  
Diagnosis And Treatment

scholarly journals Diagnostic and predictive biomarkers for lymphoma diagnosis and treatment in the era of precision medicine

2016 ◽  
Vol 29 (10) ◽  
pp. 1118-1142 ◽  
Author(s):  
Ruifang Sun ◽  
L Jeffrey Medeiros ◽  
Ken H Young
Keyword(s):  
Precision Medicine ◽  
Predictive Biomarkers ◽  
Diagnosis And Treatment
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