Precision medicine--personalized, problematic, and promising.

By J. Jameson, D. Longo. 2015

1,080 citations recorded by the source corpus.

Subfields: Cancer Research, Genetics, Pulmonary and Respiratory Medicine

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Citations in the corpus

Reinforcement Learning in Healthcare: A Survey (2019, background): “While the simplification of discretizing medicine dosage is necessary in the early proof-of-concept stage, realizing fully continuous dosing in the original action space is imperative to meet the commitments of precision medicine [96].”
Scalable and accurate deep learning with electronic health records (2018, background): “It is widely suspected that use such efforts, if successful, could provide major benefits not only for patient safety and quality but also in reducing health care costs [4, 33, 26, 42].”
A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications (2019, background): “…referred to as ‘‘personalized medicine’’), an emerging approach for disease treatment and prevention encompassing the use of new diagnostics and therapeutics, targeted to the needs of a patient based on their own genetic, biomarker, phenotypic, physical or psychosocial characteristics [113].”
A Bibliometric Analysis and Visualization of Medical Big Data Research (2018, background): “Jameson and Longo [49] from the University of Pennsylvania summarized the strengths, challenges and clinical practice of accelerated precision medicine systematically.”
Immune System Dysregulation During Spaceflight: Potential Countermeasures for Deep Space Exploration Missions (2018, background): “Environment, often considered as a combination of multiple “environmental exposures,” is defined as a “non-genetic” factor in the broad sense and is one of the three fundamental components of precision medicine: lifestyle, environment, and genetics (8).”
European Position Paper on Rhinosinusitis and Nasal Polyps 2020. (2020, methodology): “An uncontrolled study detected bacteria in 29/30 postoperative paranasal sinus specimens and 23/62 strains were coagulase-negative Staphylococcus epidermidis and 6/62 strains were Escherichia coli((155)).”
A review on longitudinal data analysis with random forest (2022, positive): “The goal of precision medicine is to provide customized treatments to patients based on their characteristics and thus to improve treatment efficiency while avoiding serious side effects [4, 25, 35].”
The Hitchhiker’s Guide to Computational Linguistics in Suicide Prevention (2021, background): “Indeed, the personalized approach is a growing trend in medicine in general (Collins & Varmus, 2015; Jameson & Longo, 2015); however, it is especially relevant to psychopathology research.”
Sex Differences in Nonalcoholic Fatty Liver Disease: State of the Art and Identification of Research Gaps (2019, background): “1459 susceptibility, phenotypes, and outcomes.(6) Sex differences have been extensively studied in recent years in fields relevant to NAFLD and its pathogenesis (Fig.”
Interpretable Dynamic Treatment Regimes (2016, background): “Precision medicine is now almost universally recognized as a path to delivering the best possible healthcare (Collins and Varmus 2015; Ashley 2015; Jameson and Longo 2015).”
Redefining Radiology: A Review of Artificial Intelligence Integration in Medical Imaging (2023, background): “The intricate insights into anatomical, physiological, and molecular disease processes provided by medical imaging have a signiﬁcant impact on patient care, facilitating the tailoring of treatments, thereby improving therapeutic outcomes and minimising adverse effects [1–3].”
Multimorbidity (2022, methodology): “Chan School of Public Health (BLSCHP-1902), Bloomberg Philanthropies (via University of North Carolina at Chapel Hill School of Public Health), FONDECYT via CIENCIACTIVA/CONCYTEC, British Council, British Embassy and the NewtonPaulet Fund (223-2018, 224-2018), DFID/ MRC/Wellcome Global Health Trials”