AIMC Topic: Sensitivity and Specificity
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LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.
International journal of computer assisted radiology and surgery
Apr 10, 2024
PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direc...
Artificial intelligence for ultrasound microflow imaging in breast cancer diagnosis.
Ultraschall in der Medizin (Stuttgart, Germany : 1980)
Apr 9, 2024
PURPOSE: To develop and evaluate artificial intelligence (AI) algorithms for ultrasound (US) microflow imaging (MFI) in breast cancer diagnosis.
Validation of Machine Learning-Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care.
Depression and anxiety
Apr 9, 2024
New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from tele...
The potential of machine learning models to identify malnutrition diagnosed by GLIM combined with NRS-2002 in colorectal cancer patients without weight loss information.
Clinical nutrition (Edinburgh, Scotland)
Apr 5, 2024
BACKGROUND & AIMS: The key step of the Global Leadership Initiative on Malnutrition (GLIM) is nutritional risk screening, while the most appropriate screening tool for colorectal cancer (CRC) patients is yet unknown. The GLIM diagnosis relies on weig...
Vaginal microbiota molecular profiling and diagnostic performance of artificial intelligence-assisted multiplex PCR testing in women with bacterial vaginosis: a single-center experience.
Frontiers in cellular and infection microbiology
Apr 5, 2024
BACKGROUND: Bacterial vaginosis (BV) is a most common microbiological syndrome. The use of molecular methods, such as multiplex real-time PCR (mPCR) and next-generation sequencing, has revolutionized our understanding of microbial communities. Here, ...
Development and evaluation of an artificial intelligence for bacterial growth monitoring in clinical bacteriology.
Journal of clinical microbiology
Apr 4, 2024
In clinical bacteriology laboratories, reading and processing of sterile plates remain a significant part of the routine workload (30%-40% of the plates). Here, an algorithm was developed for bacterial growth detection starting with any type of speci...
Automated detection of small bowel lesions based on capsule endoscopy using deep learning algorithm.
Clinics and research in hepatology and gastroenterology
Apr 4, 2024
BACKGROUND: In order to overcome the challenges of lesion detection in capsule endoscopy (CE), we improved the YOLOv5-based deep learning algorithm and established the CE-YOLOv5 algorithm to identify small bowel lesions captured by CE.
An ultrasound-based ensemble machine learning model for the preoperative classification of pleomorphic adenoma and Warthin tumor in the parotid gland.
European radiology
Apr 3, 2024
OBJECTIVES: The preoperative classification of pleomorphic adenomas (PMA) and Warthin tumors (WT) in the parotid gland plays an essential role in determining therapeutic strategies. This study aims to develop and validate an ultrasound-based ensemble...
Structural or/and functional MRI-based machine learning techniques for attention-deficit/hyperactivity disorder diagnosis: A systematic review and meta-analysis.
Journal of affective disorders
Apr 3, 2024
BACKGROUND: The aim of this study was to investigate the diagnostic value of ML techniques based on sMRI or/and fMRI for ADHD.
Application of Machine Learning for Classification of Brain Tumors: A Systematic Review and Meta-Analysis.
World neurosurgery
Apr 3, 2024
BACKGROUND: Classifying brain tumors accurately is crucial for treatment and prognosis. Machine learning (ML) shows great promise in improving tumor classification accuracy. This study evaluates ML algorithms for differentiating various brain tumor t...
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