Pragmatic and Observational Research

Dove Medical Press is pleased to invite you to submit your research to an upcoming Article Collection on "Pharmacological intervention in atrial and ventricular fibrillation: real world evidence and regulatory considerations” in Pragmatic and Observational Research edited by our journal Editor-in-Chief, Professor David Price.

In this Article Collection, Pragmatic and Observational Research hopes to shed light on the real-world effectiveness and key considerations that surround clinical interventions for atrial and ventricular fibrillation. An emphasis will be placed on real-world studies that provide significant evidence to complement data from the key phase III randomized controlled trials. Articles on non-interventional studies, administrative and claims database analyses, patient registries, electronic health records and patient surveys will be considered. Diagnostic innovations, heart monitoring approaches, big data capacities and regulatory considerations will be tackled where applicable. This collection seeks to identify drivers of progress, key barriers and real and potential solutions for clinicians and patients. The journal will pursue scholarly leadership on novel approaches within these sub-specialties. The Editors will consider Reviews, Original Research, Editorials and Reports.

Upon submission, please use the promo code VNXRA to indicate that your manuscript will be considered for this Article Collection. The deadline for manuscripts is August 31st, 2024.

For any enquiries, please email Jermaine Wilcock, Commissioning Editor at [email protected]

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Dove Medical Press is pleased to invite you to submit your research to an upcoming Article Collection on "Surgical interventions in heart valve replacement: Surgical and patient-reported outcomes” in Pragmatic and Observational Research edited by our Editor-in-Chief, Professor David Price.

In this Article Collection, Pragmatic and Observational Research hopes to shed light on the real-world effectiveness and key consideration surrounding surgical approaches to heart valve replacement, aftercare considerations, and outcomes. An emphasis will be placed on surgical outcomes, trials comparing transcatheter aortic valve implantation (TAVI) and surgical aortic valve replacement (SAVR), morbidity, mortality, bleeding complications and longer-term efficacy. This collection seeks to identify drivers of progress, key barriers and real and potential solutions for clinicians and patients. The journal will pursue scholarly leadership on novel approaches within these sub-specialties. The Editors will consider Reviews, Original Research, Editorials and Reports.

Upon submission, please use the promo code WOYHX to indicate that your manuscript will be considered for this Article Collection. The deadline for manuscripts is August 31st, 2024.

For any enquiries, please email Jermaine Wilcock, Commissioning Editor at [email protected]

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Dove Medical Press is pleased to invite you to submit your research to an upcoming Article Collection on "Optimizing patient outcomes by personalizing therapeutic management for gastrointestinal malignancies” in Pragmatic and Observational Research.

In this Article Collection, Pragmatic and Observational Research hopes to shed light on the real-world effectiveness and key considerations surrounding personalized medicine initiatives for the diagnosis and management of gastrointestinal cancers. 

Despite advancements in chemotherapy-based regimens, the clinical efficacy and survival outcomes for patients with advanced gastrointestinal malignancies remain inadequate. Such limited outcomes are due to a variety of factors that promote resistant mutations, compromise the tumor immune microenvironment, re-shape the tumor stroma to aid oncogenesis, and due to increased toxicity associated with conventional standard of care treatment approaches. Effective diagnostic and therapeutic strategies addressing these barriers should significantly optimize clinical outcomes for difficult to treat gastrointestinal cancers and are thus urgently needed. 

A Collection of reviews, original research, methodologies, analytics, modeling, clinical studies, and patient surveys evaluating the current state of clinical investigations will be organized. Please note that Pragmatic and Observational Research will no longer consider meta-analyses for publication. Studies incorporating real-world evidence via public repositories or electronic medical records originating from multiple institutions, with inclusion of under-represented populations and orphan diseases such as cholangiocarcinoma are particularly encouraged. Potential topics include but are not limited to the following: 

• Emerging therapeutic targets in gastrointestinal cancer subtypes;

• Targeted treatment selection strategies tailored towards patients with challenging hepatobiliary cancers;

• Personalized medicine approaches for the diagnosis and disease monitoring of gastrointestinal malignancies, with an emphasis on the role of ctDNA;

• Role of clinicopathological predictors of treatment response in gastrointestinal malignancies, especially colorectal cancers. 

All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisors for this Collection will not be handling the manuscripts (unless they are an Editorial Board member). Please review the journal scope and author submission instructions prior to submitting a manuscript.

Please submit your manuscript on our website, quoting the promo code HLTRH to indicate that your submission is for consideration in this Article Collection.

The deadline for submitting manuscripts is 12 April 2024. For questions about this Article Collection, including inquiries regarding discounts off of the article publishing charges, please contact Commissioning Editor Dr. MK Huffman at [email protected]. 

Guest Advisors

Khurum Khan, Honorary Associate Professor and Consultant Medical Oncologist, University College London Hospital

[email protected]

Dr. Khan is an Honorary Associate Professor and Consultant in Gastrointestinal Oncology at UCLH. He is actively involved in translational research and has presented and lectured in international conferences and public forums respectively. Dr. Khan has published several high-impact research papers in peer-reviewed journals such as Science, Cancer Discovery, Gut, Gastroenterologist, Clinical Cancer Research, Oncogene, Oncologist, BMC Cancer, Cancers, and British Journal of Cancer. He currently serves as an Associate Editor of gastroenterology section of Frontiers in Oncology. He is now a UK Chief Investigator on a phase III study at UCLH, and PI on multiple phase II/III studies. 

Umair Mahmood, Clinical Research Fellow, University College London Hospital

[email protected]

Umair Mahmood is a clinical researcher in the Department of Gastrointestinal Oncology at the University College London Hospital. He pursued additional research training in clinical trials at the Dana-Farber Cancer Institute and in radiation biology at the University of Oxford. His academic interests lie in clinical studies using targeted agents for gastrointestinal malignancies, in exploring the interplay between radiotherapy and the tumor microenvironment, and in clinical bioinformatics.

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Dove Medical Press is pleased to invite you to submit your research to an upcoming Article Collection on "Application of artificial intelligence to data management processes and predictive analysis” in Pragmatic and Observational Research.

The rightful use of artificial intelligence (AI) and machine learning (ML) approaches can accelerate our ability to leverage and extend the information contained within original, heterogeneous, and high-volume multi-omics/genomics, phenotypic, longitudinal, and healthcare data management, processing, integration, annotation, interpretation, and sharing. AI/ML have the potential to elevate recovery process with diagnostic and predictive analysis to identify major causes of mortality, modifiable risk factors, and actionable information that supports early detection and prevention of targeted disorders and sequela. Effective application of AI/ML algorithms will lead to identifying treatments that have the most potential and detecting disease development and progression through symptoms and procedures that typically precede a diagnosis to identify patients who are very likely to develop a disease. This Article Collection will focus on studies involving application of AI/ML for data management process, biomarkers discovery, and predictive analysis. 

This Article Collection features Artificial Intelligence, Machine Learning, Data Management Processes, Biomarkers Discovery, and Predictive Analysis. It invites relevant high-quality articles including reviews, original research, methodologies, analytics, modelling, clinical studies and patient surveys for transparent peer review and publication. 

All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisors for this Collection will not be handling the manuscripts (unless they are an Editorial Board member). Please review the journal scope and author submission instructions prior to submitting a manuscript.

Please submit your manuscript on our website, quoting the promo code UWZUB to indicate that your submission is for consideration in this Article Collection.

The deadline for submitting manuscripts is 31 May 2024. For questions about this Article Collection, including inquiries regarding discounts off of the article publishing charges, please contact Commissioning Editor Dr. MK Huffman at [email protected]. 

Guest Advisor

Zeeshan Ahmed, Assistant Professor, Rutgers Robert Wood Johnson Medical School, Rutgers Institute for Health, Health Care Policy and Aging Research (IFH), Rutgers, The State University of New Jersey

[email protected]

Dr. Zeeshan Ahmed is an academic computational scientist, driven towards the development of artificial intelligence (AI), machine learning (ML), and bioinformatics applications for multi-omics/genomics, phenotypic, longitudinal, and clinical data management, processing, integration, annotation, interpretation, and sharing. His lab is focused on implementing AI/M approaches for discovering significant biomarkers and predicting complex disease with high accuracy for precision medicine.

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Dove Medical Press is pleased to invite you to submit your research to an upcoming Article Collection on "Leveraging artificial intelligence to bridge research gaps and promote equity in mental health” in Pragmatic and Observational Research.

This Article Collection seeks to explore diverse aspects of mental health research conducted in real-world settings by leveraging artificial intelligence (including machine learning, deep learning, reinforcement learning, and natural language processing). Our objective is to shed light on the intersection of mental health research with real-world applications, addressing disparities, predicting risks of adverse outcomes, identifying and assessing interventions, and enhancing patient outcomes for diverse populations. 

Contributions to this Collection should encompass a broad spectrum of topics within real-world mental health research, including: 

• Observational studies, both prospective and retrospective, examining disparities in mental health outcomes among diverse populations, aiming to identify and address inequities.

• Real-world research, encompassing quantitative and qualitative methodologies, exploring the impact of social determinants of health on mental health outcomes, highlighting the interaction between environmental factors and mental well-being.

• Comparative effectiveness research evaluating psychological and pharmacological therapies for mental health disorders in real-world contexts, providing insights into their real-world efficacy and applicability.

• Development and validation of predictive models for identifying individuals at high risk of adverse mental health outcomes based on electronic medical record data, genetic markers, and social determinants of health.

• Integration of multimodal data sources, such as wearable sensors, social media activity, and environmental factors, to elucidate the complex interaction between biological, environmental, and social factors in mental health disorders.

• Application of deep learning algorithms for automated phenotyping and subtyping of mental health disorders using big data to inform personalized treatment approaches.

• Exploration of digital therapeutics and virtual reality interventions for improving access to evidence-based mental health care, particularly among underserved populations and rural communities.

• Utilization of natural language processing techniques to analyze unstructured clinical notes and patient-reported outcomes to extract valuable insights into treatment effectiveness and patient experiences.

• Investigation of disparities in mental health outcomes across demographic and socioeconomic groups through large-scale epidemiological studies using electronic medical record data and population health datasets.

• Development of decision support tools powered by artificial intelligence to assist clinicians in tailoring treatment plans, predicting treatment response, and optimizing medication management for individuals with mental health disorders.

• Examination of the impact of telepsychiatry and remote mental health services on reducing barriers to care, improving treatment adherence, and enhancing patient engagement, particularly in rural and remote areas.

• Validation studies assessing the reliability and validity of algorithms used in real-world mental health studies, ensuring robust and accurate assessment of outcomes. 

Through this Collection, we aim to develop a deeper understanding of the complex nature of mental health research and the growing importance of leveraging advanced technologies and data-driven approaches to address current challenges in mental health care delivery and outcomes.

All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisors for this Collection will not be handling the manuscripts (unless they are an Editorial Board member). Please review the journal scope and author submission instructions prior to submitting a manuscript.

Please submit your manuscript on our website, quoting the promo code RXCNV to indicate that your submission is for consideration in this Article Collection.

The deadline for submitting manuscripts is 11 October 2024. For questions about this Article Collection, including inquiries regarding discounts off of the article publishing charges, please contact Commissioning Editor Dr. MK Huffman at [email protected].

Guest Advisors

Dr. LiRong Wang, University of Pittsburgh, School of Pharmacy

[email protected]

Dr. LiRong Wang is an Assistant Professor of Pharmaceutical Sciences, School of Pharmacy at the University of Pittsburgh. His research mainly focuses on developing and applying machine/deep learning algorithms for outcome related research with electronic medical records. The diseases of interest include substance use disorder, PTSD, and Alzheimer’s diseases. 

Dr. Oshin Miranda, University of Pittsburgh, School of Pharmacy

[email protected]

Dr. Oshin Miranda received her doctorate from the University of Pittsburgh, School of Pharmacy. She is an active researcher deeply committed to leveraging advanced computational techniques, including deep learning and natural language processing, to enhance mental health related outcomes research using electronic medical records.

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