AIMC Topic: Magnetic Resonance Imaging

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Assessment of ChatGPT performance in orbital MRI reporting with multimetric evaluation of transformer based language models.

Scientific reports
Transformer-based large language models (LLMs), such as ChatGPT-4, are increasingly used to streamline clinical practice, of which radiology reporting is a prominent aspect. However, their performance in interpreting complex anatomical regions from M...

A radiomics model predicts progression from mild cognitive impairment to alzheimer's disease using structural MRI.

Scientific reports
The aim of this study is to build and validate a model based on structural magnetic resonance imaging (sMRI) to predict the progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD). A total of 343 patients with MCI were selected fro...

Preoperative prediction of the HER2 status and prognosis of patients with endometrial cancer using multiparametric MRI-based radiomics: a multicenter study.

Scientific reports
Non-invasive preoperative assessment of HER2 status is critical for identifying candidates for targeted therapy and personalizing treatment strategies in endometrial cancer (EC). This study aims to assess the preoperative value of multiparametric mag...

Non-invasive assessment techniques for renal fibrosis: advances and perspectives.

Renal failure
Renal fibrosis is a critical pathological process driving chronic kidney disease (CKD) and end-stage renal disease (ESRD). Early diagnosis is essential for timely intervention, yet traditional methods like renal biopsy are invasive and present signif...

Sustainable deep learning-based breast lesion segmentation: impact of breast region segmentation on performance.

BMC medical imaging
PURPOSE: Segmentation of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is critical for effective diagnosis. This study investigates the impact of breast region segmentation (BRS) on the performance of deep learning-...

Semi-automatic detection of anteriorly displaced temporomandibular joint discs in magnetic resonance images using machine learning.

BMC oral health
BACKGROUND: Accurate diagnosis of anterior disc displacement (ADD) is essential for managing temporomandibular joint disorders (TMJ). This study employed machine learning (ML) to automatically detect anteriorly displaced TMJ discs in magnetic resonan...

Iloprost therapy achieves good clinical and radiological short and mid-term outcomes in patients with idiopathic aseptic osteonecrosis of the knee joint also in ARCO level II.

Archives of orthopaedic and trauma surgery
AIMS: The aim of this retrospective study was the evaluation of the patient-reported and radiological outcome of intravenous Iloprost therapy in the treatment of spontaneous osteonecrosis of the knee (SONK).

Advanced deep learning-based brain tumor classification using a novel customized CNN and optimized residual network.

PloS one
The uncontrollable and rapid growth of brain cells can lead to brain tumors. If left untreated, this condition may result in severe health consequences, including death. Accurate detection and classification are the essential steps toward understandi...

Machine learning-based estimation of the mild cognitive impairment stage using multimodal physical and behavioral measures.

Scientific reports
Mild cognitive impairment (MCI) is a prodromal stage of dementia, and its early detection is critical for improving clinical outcomes. However, current diagnostic tools such as brain magnetic resonance imaging (MRI) and neuropsychological testing hav...

IoMT driven Alzheimer's prediction model empowered with transfer learning and explainable AI approach in healthcare 5.0.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the primary cause of dementia, responsible for 60-70% of global cases. It severely affects memory, cognitive function, and daily independence, placing a substantial emotional an...