AIMC Topic: Humans

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A survey on open challenges in heart disease prediction models.

Computational biology and chemistry
Heart disease (HD), is a deadly serious disease, that has received a great deal of consideration in medical study. A lot of prompting factors like professional, as well as personal behaviors and genetic nature, are accountable for the occurrence of H...

Diagnostic Performance of Artificial Intelligence Based on Biparametric MRI for Clinically Significant Prostate Cancer: A Systematic Review and Meta-analysis.

Academic radiology
OBJECTIVES: This meta-analysis aimed to systematically evaluate the diagnostic performance of artificial intelligence (AI) applied to biparametric magnetic resonance imaging (bpMRI) for identifying clinically significant prostate cancer (csPCa).

Harnessing Artificial Intelligence for Precision Diagnosis and Treatment of Triple Negative Breast Cancer.

Clinical breast cancer
Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer (BC) characterized by the absence of estrogen, progesterone, and HER2 receptors, resulting in limited therapeutic options. This article critically examines the role ...

Patient consent for the secondary use of health data in artificial intelligence (AI) models: A scoping review.

International journal of medical informatics
BACKGROUND: The secondary use of health data for training Artificial Intelligence (AI) models holds immense potential for advancing medical research and healthcare delivery. However, ensuring patient consent for such utilization is paramount to uphol...

Predictive value of machine learning for in-hospital mortality risk in acute myocardial infarction: A systematic review and meta-analysis.

International journal of medical informatics
BACKGROUND: Machine learning (ML) models have been constructed to predict the risk of in-hospital mortality in patients with myocardial infarction (MI). Due to diverse ML models and modeling variables, along with the significant imbalance in data, th...

Awareness of the Role of Artificial Intelligence in Health Care among Undergraduate Nursing Students: A Descriptive Cross-Ssectional Study.

Nurse education today
BACKGROUND: Artificial intelligence (AI) has the potential to revolutionize healthcare by improving efficiency and reducing errors; however, challenges such as inadequate funding and lack of awareness among healthcare professionals hinder its integra...

Artificial intelligence and whole slide imaging, a new tool for the microsatellite instability prediction in colorectal cancer: Friend or foe?

Critical reviews in oncology/hematology
Colorectal cancer (CRC) is the third most common and second most deadly cancer worldwide. Despite advances in screening and treatment, CRC is heterogeneous and the response to therapy varies significantly, limiting personalized treatment options. Cer...

DGEDDGAN: A dual-domain generator and edge-enhanced dual discriminator generative adversarial network for MRI reconstruction.

Magnetic resonance imaging
Magnetic resonance imaging (MRI) as a critical clinical tool in medical imaging, requires a long scan time for producing high-quality MRI images. To accelerate the speed of MRI while reconstructing high-quality images with sharper edges and fewer ali...

Diagnostic value of deep learning of multimodal imaging of thyroid for TI-RADS category 3-5 classification.

Endocrine
BACKGROUND: Thyroid nodules classified within the Thyroid Imaging Reporting and Data Systems (TI-RADS) category 3-5 are typically regarded as having varying degrees of malignancy risk, with the risk increasing from TI-RADS 3 to TI-RADS 5. While some ...

Assessment of CNNs, transformers, and hybrid architectures in dental image segmentation.

Journal of dentistry
OBJECTIVES: Convolutional Neural Networks (CNNs) have long dominated image analysis in dentistry, reaching remarkable results in a range of different tasks. However, Transformer-based architectures, originally proposed for Natural Language Processing...