AIMC Topic: Reproducibility of Results

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Small groups in multidimensional feature space: Two examples of supervised two-group classification from biomedicine.

Journal of bioinformatics and computational biology
Some biomedical datasets contain a small number of samples which have large numbers of features. This can make analysis challenging and prone to errors such as overfitting and misinterpretation. To improve the accuracy and reliability of analysis in ...

Deep Learning for Pneumothorax Detection on Chest Radiograph: A Diagnostic Test Accuracy Systematic Review and Meta Analysis.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
BACKGROUND: Pneumothorax is a common acute presentation in healthcare settings. A chest radiograph (CXR) is often necessary to make the diagnosis, and minimizing the time between presentation and diagnosis is critical to deliver optimal treatment. De...

Reliability of large language models in managing odontogenic sinusitis clinical scenarios: a preliminary multidisciplinary evaluation.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: This study aimed to evaluate the utility of large language model (LLM) artificial intelligence tools, Chat Generative Pre-Trained Transformer (ChatGPT) versions 3.5 and 4, in managing complex otolaryngological clinical scenarios, specificall...

Uncovering hidden treasures: Mapping morphological changes in the differentiation of human mesenchymal stem cells to osteoblasts using deep learning.

Micron (Oxford, England : 1993)
Deep Learning (DL) is becoming an increasingly popular technology being employed in life sciences research due to its ability to perform complex and time-consuming tasks with significantly greater speed, accuracy, and reproducibility than human resea...

Is ChatGPT a reliable source of scientific information regarding third-molar surgery?

Journal of the American Dental Association (1939)
BACKGROUND: ChatGPT (OpenAI) is a large language model. This model uses artificial intelligence and machine learning techniques to generate humanlike language and responses, even to complex questions. The authors aimed to assess the reliability of re...

Comparison of deep learning networks for fully automated head and neck tumor delineation on multi-centric PET/CT images.

Radiation oncology (London, England)
OBJECTIVES: Deep learning-based auto-segmentation of head and neck cancer (HNC) tumors is expected to have better reproducibility than manual delineation. Positron emission tomography (PET) and computed tomography (CT) are commonly used in tumor segm...

Application of a human-centered design for embedded machine learning model to develop data labeling software with nurses: Human-to-Artificial Intelligence (H2AI).

International journal of medical informatics
BACKGROUND: Nurses are essential for assessing and managing acute pain in hospitalized patients, especially those who are unable to self-report pain. Given their role and subject matter expertise (SME), nurses are also essential for the design and de...

Seeing through a robot's eyes: A cross-sectional exploratory study in developing a robotic screening technology for autism.

Autism research : official journal of the International Society for Autism Research
The present exploratory cross-sectional case-control study sought to develop a reliable and scalable screening tool for autism using a social robot. The robot HUMANE, installed with computer vision and linked with recognition technology, detected the...

Assessing the impact of occlusal plane rotation on facial aesthetics in orthodontic treatment: a machine learning approach.

BMC oral health
BACKGROUND: Adequate occlusal plane (OP) rotation through orthodontic therapy enables satisfying profile improvements for patients who are disturbed by their maxillomandibular imbalance but reluctant to surgery. The study aims to quantify profile imp...

Enhancing Ki-67 Prediction in Breast Cancer: Integrating Intratumoral and Peritumoral Radiomics From Automated Breast Ultrasound via Machine Learning.

Academic radiology
RATIONALE AND OBJECTIVES: Traditional Ki-67 evaluation in breast cancer (BC) via core needle biopsy is limited by repeatability and heterogeneity. The automated breast ultrasound system (ABUS) offers reproducibility but is constrained to morphologica...