AIMC Topic: Aged

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Deep Learning-Based Reconstruction of 3D T1 SPACE Vessel Wall Imaging Provides Improved Image Quality with Reduced Scan Times: A Preliminary Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Intracranial vessel wall imaging is technically challenging to implement, given the simultaneous requirements of high spatial resolution, excellent blood and CSF signal suppression, and clinically acceptable gradient times. He...

Prediction of Healing Trajectory of Chronic Wounds Using a Machine Learning Approach.

Advances in wound care
New treatment options are emerging for chronic wounds, which represent a growing problem because of population ageing and increasing burden of chronic disease. While promising, the existing evidence for advanced modalities is commonly derived from s...

Chest computed tomography-based artificial intelligence-aided latent class analysis for diagnosis of severe pneumonia.

Chinese medical journal
BACKGROUND: There is little literature describing the artificial intelligence (AI)-aided diagnosis of severe pneumonia (SP) subphenotypes and the association of the subphenotypes with the ventilatory treatment efficacy. The aim of our study is to ill...

Utilizing artificial intelligence to determine bone mineral density using spectral CT.

Bone
BACKGROUND: Dual-energy computed tomography (DECT) has demonstrated the feasibility of using HAP-water to respond to BMD changes without requiring dedicated software or calibration. Artificial intelligence (AI) has been utilized for diagnosising oste...

Validation of an artificial intelligence-based prognostic biomarker in patients with oligometastatic Castration-Sensitive prostate cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND: There is a need for clinically actionable prognostic and predictive tools to guide the management of oligometastatic castration-sensitive prostate cancer (omCSPC).

Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.

International journal of environmental research and public health
Feature selection is essentially the process of picking informative and relevant features from a larger collection of features. Few studies have focused on predictors for current e-cigarette use among U.S. adults using feature selection and machine l...

Machine learning models in evaluating the malignancy risk of ovarian tumors: a comparative study.

Journal of ovarian research
OBJECTIVES: The study aimed to compare the diagnostic efficacy of the machine learning models with expert subjective assessment (SA) in assessing the malignancy risk of ovarian tumors using transvaginal ultrasound (TVUS).

Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis.

BMC medical informatics and decision making
BACKGROUND: In older adults with hypertension, hip fractures accompanied by preoperative acute heart failure significantly elevate surgical risks and adverse outcomes, necessitating timely identification and management to improve patient outcomes.

Computed tomography enterography radiomics and machine learning for identification of Crohn's disease.

BMC medical imaging
BACKGROUND: Crohn's disease is a severe chronic and relapsing inflammatory bowel disease. Although contrast-enhanced computed tomography enterography is commonly used to evaluate crohn's disease, its imaging findings are often nonspecific and can ove...