Cough-based diagnosis for respiratory diseases (RDs) using artificial intelligence (AI) has attracted considerable attention, yet many existing studies overlook confounding variables in their predictive models. These variables can distort the relationship between cough recordings (input data) and RD status (output variable), leading to biased associations and unrealistic model performance. To address this gap, we propose the Bias-Free Network (RBF-Net), an end-to-end solution that effectively mitigates the impact of confounders in the training data distribution. RBF-Net ensures accurate and unbiased RD diagnosis features, emphasizing its relevance by incorporating a COVID-19 dataset in this study. This approach aims to enhance the reliability of AI-based RD diagnosis models by navigating the challenges posed by confounding variables. A hybrid of a Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks is proposed for the feature encoder module of RBF-Net. An additional bias predictor is incorporated in the classification scheme to formulate a conditional Generative Adversarial Network (c-GAN) that helps in decorrelating the impact of confounding variables from RD prediction. The merit of RBF-Net is demonstrated by comparing classification performance with a State-of-The-Art (SoTA) Deep Learning (DL) model (CNN-LSTM) after training on different unbalanced COVID-19 data sets, created by using a large-scale proprietary cough data set. RBF-Net proved its robustness against extremely biased training scenarios by achieving test set accuracies of 84.1%, 84.6%, and 80.5% for the following confounding variables-gender, age, and smoking status, respectively. RBF-Net outperforms the CNN-LSTM model test set accuracies by 5.5%, 7.7%, and 8.2%, respectively.
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http://dx.doi.org/10.3390/bioengineering11010055 | DOI Listing |
Eur J Epidemiol
January 2025
Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Stockholm, Sweden.
The Stockholm Early Detection of Cancer Study (STEADY-CAN) cohort was established to investigate strategies for early cancer detection in a population-based context within Stockholm County, the capital region of Sweden. Utilising real-world data to explore cancer-related healthcare patterns and outcomes, the cohort links extensive clinical and laboratory data from both inpatient and outpatient care in the region. The dataset includes demographic information, detailed diagnostic codes, laboratory results, prescribed medications, and healthcare utilisation data.
View Article and Find Full Text PDFAm J Obstet Gynecol MFM
January 2025
Department of Obstetrics and Gynecology, Emek Medical Center, Afula, Israel; Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.
Objective: Post-cesarean delivery (CD) acute pain may progress to chronic pain, which may impair maternal bonding and child development. In 2013, we compared the efficacy of versus on-demand oral analgesia for post-caesarean pain in a randomized-controlled-trial. The fixed-time-interval group had received scheduled paracetamol, tramadol, and diclofenac regardless of pain level, and the on-demand group received medication as needed, with oxycodone reserved for unrelieved pain in both groups.
View Article and Find Full Text PDFJ Clin Anesth
January 2025
Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA. Electronic address:
Study Objective: To assess whether, in a lung resection cohort with a low probability of confounding by indication, higher FiO is associated with an increased risk of impaired postoperative oxygenation - a clinical manifestation of lung injury/dysfunction.
Design: Pre-specified registry-based retrospective cohort study.
Setting: Two large academic hospitals in the United States.
Am J Sports Med
January 2025
Department of Orthopaedic Surgery, Mayo Clinic, Phoenix, Arizona, USA.
Background: Tobacco use is a known modifiable risk factor for postoperative complications and revision surgery after anterior cruciate ligament reconstruction (ACLR). Previous studies focus on tobacco as a broad categorization of traditional smoking, smokeless tobacco, and other forms of nicotine use. It is unclear if differences in the type of nicotine used lead to similar adverse outcomes after ACLR.
View Article and Find Full Text PDFJ Cosmet Dermatol
January 2025
Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
Background: The skin microbiota, a complex community of microorganisms residing on the skin, plays a crucial role in maintaining skin health and overall homeostasis. Recent research has suggested that alterations in the composition and function of the skin microbiota may influence the aging process. However, the causal relationships between specific skin microbiota and biological aging remain unclear.
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