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Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study

Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study

The deep learning algorithm was designed to automatically delineate the GTV from chest CT images of patients with lung cancer who underwent radiotherapy treatment. The underlying FL infrastructure architecture was designed to securely perform deep learning training and was tested for vulnerabilities from known security threats. This paper predominantly discussed the FL infrastructure architecture and presented a firsthand experience of conducting such studies.

Ananya Choudhury, Leroy Volmer, Frank Martin, Rianne Fijten, Leonard Wee, Andre Dekker, Johan van Soest

JMIR AI 2025;4:e60847

The Transformative Potential of Large Language Models in Mining Electronic Health Records Data: Content Analysis

The Transformative Potential of Large Language Models in Mining Electronic Health Records Data: Content Analysis

JSON: Java Script object notation; RT: radiotherapy. Motivated by the capabilities of LLMs, we aimed to investigate their potential application in extracting and structuring information from clinical reports. Our overarching objective is to integrate LLM-based tools into our information system, enhancing the richness of our real-world datasets.

Amadeo Jesus Wals Zurita, Hector Miras del Rio, Nerea Ugarte Ruiz de Aguirre, Cristina Nebrera Navarro, Maria Rubio Jimenez, David Muñoz Carmona, Carlos Miguez Sanchez

JMIR Med Inform 2025;13:e58457

Real-World Survival Comparisons Between Radiotherapy and Surgery for Metachronous Second Primary Lung Cancer and Predictions of Lung Cancer–Specific Outcomes Using Machine Learning: Population-Based Study

Real-World Survival Comparisons Between Radiotherapy and Surgery for Metachronous Second Primary Lung Cancer and Predictions of Lung Cancer–Specific Outcomes Using Machine Learning: Population-Based Study

Stereotactic body radiotherapy has recently been reported to have similar survival outcomes as surgery in patients with early-stage lung cancer [10,11]. Previous studies have shown that radiotherapy is a safe and feasible treatment for MSPLC, but whether it can compare with surgery in terms of survival outcomes remains debated [12,13].

Yue Zheng, Ailin Zhao, Yuqi Yang, Laduona Wang, Yifei Hu, Ren Luo, Yijun Wu

JMIR Cancer 2024;10:e53354

Holistic Person-Centered Care in Radiotherapy: Protocol for a Scoping Review

Holistic Person-Centered Care in Radiotherapy: Protocol for a Scoping Review

Radiotherapy is considered a conservative form of treatment with reduced adverse effects, unlike other treatments such as surgery, which can have mutilating and other long-term adverse effects, thus maintaining a good quality of life [6]. Evidence-based practice shows that more than 50% of patients with cancer will undergo a course of radiotherapy as part of their treatment, and despite this, patients appear to lack knowledge of the importance of radiotherapy treatment and its effects [7,8].

Fatima Bhyat, Andrew Makkink, Karien Henrico

JMIR Res Protoc 2024;13:e51338

Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study

Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study

We aimed to develop a prediction model for early identification of patients at risk for depression within the first month of chemo- or radiotherapy treatment. We assessed the relevance of different data modalities for predictive performance in a retrospective cohort study. This retrospective observational study used data from the integration of 3 health care organizations: an academic medical center (AMC), a primary and specialty care alliance (PSC), and a community medical center (CMC).

Anne de Hond, Marieke van Buchem, Claudio Fanconi, Mohana Roy, Douglas Blayney, Ilse Kant, Ewout Steyerberg, Tina Hernandez-Boussard

JMIR Med Inform 2024;12:e51925

App-Controlled Treatment Monitoring and Support for Patients With Head and Neck Cancer Undergoing Radiotherapy: Results From a Prospective Randomized Controlled Trial

App-Controlled Treatment Monitoring and Support for Patients With Head and Neck Cancer Undergoing Radiotherapy: Results From a Prospective Randomized Controlled Trial

Treatment for nonmetastatic HNC depends on disease stage and localization and usually requires multimodal approaches comprising surgery, radiotherapy, and concomitant systemic treatments [2-4]. Within the treatment context, radiotherapy is a therapeutic mainstay, both as a primary treatment for patients with HNC and as an adjuvant therapy after surgery in case of locoregionally advanced cancers or increased risk of tumor recurrence [5-7].

Tanja Sprave, Michelle Pfaffenlehner, Raluca Stoian, Eleni Christofi, Alexander Rühle, Daniela Zöller, Alexander Fabian, Harald Fahrner, Harald Binder, Henning Schäfer, Eleni Gkika, Anca-Ligia Grosu, Felix Heinemann, Nils Henrik Nicolay

J Med Internet Res 2023;25:e46189

Effects of Semisupervised Exercise Training on Health Outcomes in People With Lung or Head and Neck Cancer: Protocol for a Randomized Controlled Trial

Effects of Semisupervised Exercise Training on Health Outcomes in People With Lung or Head and Neck Cancer: Protocol for a Randomized Controlled Trial

The usual cancer treatment options are surgery, chemotherapy, radiotherapy, or a combination of these treatments [4]. Although having positive effects, these treatments also have side effects, such as fatigue [5,6] and a decrease in functional exercise capacity [7], muscle mass [8], and muscle strength [8,9], which will ultimately affect physical activity and health-related quality of life (HRQo L) [10,11]. Therefore, complementary interventions that could minimize these side effects are needed [7].

Isis Grigoletto, Vinicius Cavalheri, Luis Alberto Gobbo, Karina Pozo, Enio Rodrigues Maia Filho, Diogo Gonçalves Ribeiro, Nara Ielo, Fabiano Francisco De Lima, Ercy Mara Cipulo Ramos

JMIR Res Protoc 2023;12:e43547

A Scalable Radiomics- and Natural Language Processing–Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study

A Scalable Radiomics- and Natural Language Processing–Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study

Most patients with cancer with bone metastasis (BM) experience pain [1] and most receive radiotherapy to control it [2]. But, it has been shown that due to the subjective and qualitative nature of the pain, clinicians often underestimate pain [3]. As a result, many patients with BM receive radiotherapy after their pain has already become debilitating [4].

Hossein Naseri, Sonia Skamene, Marwan Tolba, Mame Daro Faye, Paul Ramia, Julia Khriguian, Marc David, John Kildea

JMIR AI 2023;2:e44779