AIMC Topic: Middle Aged

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A transparent machine learning algorithm uncovers HbA1c patterns associated with therapeutic inertia in patients with type 2 diabetes and failure of metformin monotherapy.

International journal of medical informatics Jul 15, 2024
AIMS: This study aimed to identify and categorize the determinants influencing the intensification of therapy in Type 2 Diabetes (T2D) patients with suboptimal blood glucose control despite metformin monotherapy.
Metformin Treatment Failure Blood Glucose Diabetes Mellitus, Type 2 Hypoglycemic Agents Glycated Hemoglobin Humans Machine Learning Algorithms Electronic Health Records Female Aged Male Middle Aged
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Novel Artificial Intelligence Combining Convolutional Neural Network and Support Vector Machine to Predict Colorectal Cancer Prognosis and Mutational Signatures From Hematoxylin and Eosin Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Jul 15, 2024
Reducing recurrence following radical resection of colon cancer without overtreatment or undertreatment remains a challenge. Postoperative adjuvant chemotherapy (Adj) is currently administered based solely on pathologic TNM stage. However, prognosis ...
Neoplasm Recurrence, Local Eosine Yellowish-(YS) Hematoxylin Prognosis Female Aged Colorectal Neoplasms Support Vector Machine Neoplasm Staging Mutation Humans Male Neural Networks, Computer Middle Aged Artificial Intelligence
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Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach.

Journal of cachexia, sarcopenia and muscle Jul 15, 2024
BACKGROUND: There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with the progression of i...
Humans Phenotype Retrospective Studies Adipose Tissue Middle Aged Glucose Deep Learning Whole Body Imaging Magnetic Resonance Imaging Female Muscle, Skeletal Aged Adult Male
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Deep learning reconstructed T2-weighted Dixon imaging of the spine: Impact on acquisition time and image quality.

European journal of radiology Jul 15, 2024
PURPOSE: To assess the image quality and impact on acquisition time of a novel deep learning based T2 Dixon sequence (T2) of the spine.
Male Middle Aged Deep Learning Magnetic Resonance Imaging Humans Prospective Studies Female Lumbar Vertebrae Aged Image Interpretation, Computer-Assisted Adult Artifacts Spinal Diseases
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Artificial intelligence-based computer-aided diagnosis abnormality score trends in the serial mammography of patients with breast cancer.

European journal of radiology Jul 15, 2024
PURPOSE: To explore the abnormality score trends of artificial intelligence-based computer-aided diagnosis (AI-CAD) in the serial mammography of patients until a final diagnosis of breast cancer.
Humans Artificial Intelligence Retrospective Studies Female Aged Adult Radiographic Image Interpretation, Computer-Assisted Breast Neoplasms Middle Aged Diagnosis, Computer-Assisted Mammography
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Machine learning-based prediction of diabetic patients using blood routine data.

Methods (San Diego, Calif.) Jul 15, 2024
Diabetes stands as one of the most prevalent chronic diseases globally. The conventional methods for diagnosing diabetes are frequently overlooked until individuals manifest noticeable symptoms of the condition. This study aimed to address this gap b...
Male Middle Aged ROC Curve Diabetes Mellitus Support Vector Machine Erythrocyte Indices Machine Learning Algorithms Female Adult Humans
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Development and validation of 10-year risk prediction models of cardiovascular disease in Chinese type 2 diabetes mellitus patients in primary care using interpretable machine learning-based methods.

Diabetes, obesity & metabolism Jul 15, 2024
AIM: To develop 10-year cardiovascular disease (CVD) risk prediction models in Chinese patients with type 2 diabetes mellitus (T2DM) managed in primary care using machine learning (ML) methods.
Adult Male Cardiovascular Diseases Middle Aged Retrospective Studies Female Risk Factors Aged Follow-Up Studies East Asian People Risk Assessment China Primary Health Care Diabetes Mellitus, Type 2 Humans Machine Learning
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Assessment of image quality and diagnostic accuracy for cervical spondylosis using T2w-STIR sequence with a deep learning-based reconstruction approach.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Jul 15, 2024
OBJECTIVES: To investigate potential of enhancing image quality, maintaining interobserver consensus, and elevating disease diagnostic efficacy through the implementation of deep learning-based reconstruction (DLR) processing in 3.0 T cervical spine ...
Cervical Vertebrae Spondylosis Middle Aged Deep Learning Image Processing, Computer-Assisted Humans Female Magnetic Resonance Imaging Aged Adult Male
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Predictive Modeling of Long-Term Prognosis After Resection in Typical Pulmonary Carcinoid: A Machine Learning Perspective.

Cancer investigation Jul 15, 2024
Typical Pulmonary Carcinoid (TPC) is defined by its slow growth, frequently necessitating surgical intervention. Despite this, the long-term outcomes following tumor resection are not well understood. This study examined the factors impacting Overall...
Humans Machine Learning Male Middle Aged Prognosis Lung Neoplasms Female SEER Program Aged Carcinoid Tumor Adult
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[Relationship between certain uses of artificial intelligence and psychosocial risk factors in European work environments].

Archivos de prevencion de riesgos laborales Jul 15, 2024
INTRODUCTION: To examine the relationship between the use of Artificial Intelligence (AI) to assess and monitor job performance and exposure to psychosocial risk factors, as well as associated adverse health effects in the European work environment.
Middle Aged Young Adult Humans Workplace Europe Adult Artificial Intelligence Occupational Stress Cross-Sectional Studies Workload Female Working Conditions Male Occupational Health Risk Factors
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