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Development and validation of interpretable machine learning models for postoperative pneumonia prediction.
Frontiers in public health
Dec 11, 2024
BACKGROUND: Postoperative pneumonia, a prevalent form of hospital-acquired pneumonia, poses significant risks to patients' prognosis and even their lives. This study aimed to develop and validate a predictive model for postoperative pneumonia in surg...
Digital Pathology-based Artificial Intelligence Biomarker Validation in Metastatic Prostate Cancer.
European urology oncology
Dec 10, 2024
BACKGROUND AND OBJECTIVE: Owing to the expansion of treatment options for metastatic hormone-sensitive prostate cancer (mHSPC) and an appreciation of clinical subgroups with differential prognosis and treatment responses, prognostic and predictive bi...
Evaluating the efficacy of AI systems in diabetic retinopathy detection: A comparative analysis of Mona DR and IDx-DR.
Acta ophthalmologica
Dec 10, 2024
PURPOSE: To compare two artificial intelligence (AI)-based Automated Diabetic Retinopathy Image Assessment (ARIA) softwares in terms of concordance with specialist human graders and referable diabetic retinopathy (DR) diagnostic capacity.
Machine Learning Reveals Demographic Disparities in Palliative Care Timing Among Patients With Traumatic Brain Injury Receiving Neurosurgical Consultation.
Neurocritical care
Dec 10, 2024
BACKGROUND: Timely palliative care (PC) consultations offer demonstrable benefits for patients with traumatic brain injury (TBI), yet their implementation remains inconsistent. This study employs machine learning methods to identify distinct patient ...
Enhancing thin slice 3D T2-weighted prostate MRI with super-resolution deep learning reconstruction: Impact on image quality and PI-RADS assessment.
Magnetic resonance imaging
Dec 10, 2024
PURPOSES: This study aimed to assess the effectiveness of Super-Resolution Deep Learning Reconstruction (SR-DLR) -a deep learning-based technique that enhances image resolution and quality during MRI reconstruction- in improving the image quality of ...
Subtyping strokes using blood-based protein biomarkers: A high-throughput proteomics and machine learning approach.
European journal of clinical investigation
Dec 10, 2024
BACKGROUND: Rapid diagnosis of stroke and its subtypes is critical in early stages. We aimed to discover and validate blood-based protein biomarkers to differentiate ischemic stroke (IS) from intracerebral haemorrhage (ICH) using high-throughput prot...
Preliminary findings regarding the association between patient demographics and ED experience scores across a regional health system: A cross sectional study using natural language processing of patient comments.
International journal of medical informatics
Dec 10, 2024
OBJECTIVE: Existing literature shows associations between patient demographics and reported experiences of care, but this relationship is poorly understood. Our objective was to use natural language processing of patient comments to gain insight into...
Non-invasive Prediction of Lymph Node Metastasis in NSCLC Using Clinical, Radiomics, and Deep Learning Features From F-FDG PET/CT Based on Interpretable Machine Learning.
Academic radiology
Dec 10, 2024
PURPOSE: This study aimed to develop and evaluate a machine learning model combining clinical, radiomics, and deep learning features derived from PET/CT imaging to predict lymph node metastasis (LNM) in patients with non-small cell lung cancer (NSCLC...
MRI classification of progressive supranuclear palsy, Parkinson disease and controls using deep learning and machine learning algorithms for the identification of regions and tracts of interest as potential biomarkers.
Computers in biology and medicine
Dec 10, 2024
BACKGROUND: Quantitative magnetic resonance imaging (MRI) analysis has shown promise in differentiating neurodegenerative Parkinsonian syndromes and has significantly advanced our understanding of diseases like progressive supranuclear palsy (PSP) in...
Development and validation of a deep learning model for morphological assessment of myeloproliferative neoplasms using clinical data and digital pathology.
British journal of haematology
Dec 10, 2024
The subjectivity of morphological assessment and the overlapping pathological features of different subtypes of myeloproliferative neoplasms (MPNs) make accurate diagnosis challenging. To improve the pathological assessment of MPNs, we developed a di...
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