AIMC Topic: Adult
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Continuous nursing symptom management in cancer chemotherapy patients using deep learning.
Scientific reports
Mar 7, 2025
To assess the efficacy of a deep learning platform for managing symptoms in chemotherapy patients, aiming to enhance their quality of life. A non-randomized controlled trial was conducted from September 2022 to March 2024, involving 144 chemotherapy ...
Prognostic model for log odds of negative lymph node in locally advanced rectal cancer via interpretable machine learning.
Scientific reports
Mar 7, 2025
No studies have examined the prognostic value of the log odds of negative lymph nodes/T stage (LONT) in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (nCRT). We aimed to assess the prognostic value of LONT and devel...
Explainable multiscale temporal convolutional neural network model for sleep stage detection based on electroencephalogram activities.
Journal of neural engineering
Mar 7, 2025
Humans spend a significant portion of their lives in sleep (an essential driver of body metabolism). Moreover, as sleep deprivation could cause various health complications, it is crucial to develop an automatic sleep stage detection model to facilit...
Algorithm, expert, or both? Evaluating the role of feature selection methods on user preferences and reliance.
PloS one
Mar 7, 2025
The integration of users and experts in machine learning is a widely studied topic in artificial intelligence literature. Similarly, human-computer interaction research extensively explores the factors that influence the acceptance of AI as a decisio...
The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning Applications.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 7, 2025
The last decade has witnessed a notable surge in deep learning applications for electroencephalography (EEG) data analysis, showing promising improvements over conventional statistical techniques. However, deep learning models can underperform if tra...
Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease.
Gut microbes
Mar 6, 2025
Diabetic kidney disease (DKD) is a serious healthcare dilemma. Nonetheless, the interplay between the functional capacity of gut microbiota and their host remains elusive for DKD. This study aims to elucidate the functional capability of gut microbio...
Counting coins in the dark-Austrian, German, and Swiss medical students' perceptions of radiology.
European radiology
Mar 6, 2025
OBJECTIVES: To investigate the overall attitude of medical students towards radiology, their perceptions of the university curriculum, the clinical relevance, and the prospects within the specialty, as well as identify reasons for and against choosin...
A Preoperative CT-based Multiparameter Deep Learning and Radiomic Model with Extracellular Volume Parameter Images Can Predict the Tumor Budding Grade in Rectal Cancer Patients.
Academic radiology
Mar 6, 2025
RATIONALE AND OBJECTIVES: To investigate a computed tomography (CT)-based multiparameter deep learning-radiomic model (DLRM) for predicting the preoperative tumor budding (TB) grade in patients with rectal cancer.
Development of artificial intelligence-based algorithms for the process of human identification through dental evidence.
International journal of legal medicine
Mar 6, 2025
INTRODUCTION: Forensic Odontology plays a crucial role in medicolegal identification by comparing dental evidence in antemortem (AM) and postmortem (PM) dental records, including orthopantomograms (OPGs). Due to the complexity and time-consuming natu...
Development of a natural language processing algorithm to extract social determinants of health from clinician notes.
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Mar 6, 2025
Disparities in access to the organ transplant waitlist are well-documented, but research into modifiable factors has been limited due to a lack of access to organized prewaitlisting data. This study aimed to develop a natural language processing (NLP...
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