AIMC Topic: Reproducibility of Results

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A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

Progress in biophysics and molecular biology
The risk of discovering an intracranial aneurysm during the initial screening and follow-up screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these mass effects, unruptured aneurysms frequently generate symptoms, how...

ChatGPT vs Google for Queries Related to Dementia and Other Cognitive Decline: Comparison of Results.

Journal of medical Internet research
BACKGROUND: People living with dementia or other cognitive decline and their caregivers (PLWD) increasingly rely on the web to find information about their condition and available resources and services. The recent advancements in large language mode...

Psychometric evaluation of Persian version of medical artificial intelligence readiness scale for medical students.

BMC medical education
BACKGROUND: Artificial intelligence's advancement in medicine and its worldwide implementation will be one of the main elements of medical education in the coming years. This study aimed to translate and psychometric evaluation of the Persian version...

Validation of bone mineral density measurement using quantitative CBCT image based on deep learning.

Scientific reports
The bone mineral density (BMD) measurement is a direct method of estimating human bone mass for diagnosing osteoporosis, and performed to objectively evaluate bone quality before implant surgery in dental clinics. The objective of this study was to v...

A Dual Architecture Fusion and AutoEncoder for Automatic Morphological Classification of Human Sperm.

Sensors (Basel, Switzerland)
Infertility has become a common problem in global health, and unsurprisingly, many couples need medical assistance to achieve reproduction. Many human behaviors can lead to infertility, which is none other than unhealthy sperm. The important thing is...

Development of a deep learning-based model to diagnose mixed-type gastric cancer accurately.

The international journal of biochemistry & cell biology
OBJECTIVE: The accurate diagnosis of mixed-type gastric cancer from pathology images presents a formidable challenge for pathologists, given its intricate features and resemblance to other subtypes of gastric cancer. Artificial Intelligence has the p...

Robotic ultrasound imaging: State-of-the-art and future perspectives.

Medical image analysis
Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Rob...

A simple and reliable instance selection for fast training support vector machine: Valid Border Recognition.

Neural networks : the official journal of the International Neural Network Society
Support vector machines (SVMs) are powerful statistical learning tools, but their application to large datasets can cause time-consuming training complexity. To address this issue, various instance selection (IS) approaches have been proposed, which ...

Topological deep learning based deep mutational scanning.

Computers in biology and medicine
High-throughput deep mutational scanning (DMS) experiments have significantly impacted protein engineering, drug discovery, immunology, cancer biology, and evolutionary biology by enabling the systematic understanding of protein functions. However, t...

Deep learning-based prediction of H3K27M alteration in diffuse midline gliomas based on whole-brain MRI.

Cancer medicine
BACKGROUND: H3K27M mutation status significantly affects the prognosis of patients with diffuse midline gliomas (DMGs), but this tumor presents a high risk of pathological acquisition. We aimed to construct a fully automated model for predicting the ...