AIMC Topic: Artificial Intelligence

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A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis.

JAMA network open
IMPORTANCE: An accurate and robust artificial intelligence (AI) algorithm for detecting cancer in digital breast tomosynthesis (DBT) could significantly improve detection accuracy and reduce health care costs worldwide.

Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations.

JAMA network open
IMPORTANCE: Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for earlier prevention research. Artificial intelligence may facilitate early detection of SARS-CoV2 emergi...

Accuracy and Time Comparison Between Side-by-Side and Artificial Intelligence Overlayed Images.

Ophthalmic surgery, lasers & imaging retina
BACKGROUND AND OBJECTIVE: The purpose of this study was to evaluate the accuracy and the time to find a lesion, taken in different platforms, color fundus photographs and infrared scanning laser ophthalmoscope images, using the traditional side-by-si...

Vertical Nystagmus Recognition Based on Deep Learning.

Sensors (Basel, Switzerland)
Vertical nystagmus is a common neuro-ophthalmic sign in vestibular medicine. Vertical nystagmus not only reflects the functional state of vertical semicircular canal but also reflects the effect of otoliths. Medical experts can take nystagmus symptom...

Precision Medicine in Glaucoma: Artificial Intelligence, Biomarkers, Genetics and Redox State.

International journal of molecular sciences
Glaucoma is a multifactorial neurodegenerative illness requiring early diagnosis and strict monitoring of the disease progression. Current exams for diagnosis and prognosis are based on clinical examination, intraocular pressure (IOP) measurements, v...

Comparison of Chest Radiograph Captions Based on Natural Language Processing vs Completed by Radiologists.

JAMA network open
IMPORTANCE: Artificial intelligence (AI) can interpret abnormal signs in chest radiography (CXR) and generate captions, but a prospective study is needed to examine its practical value.

Hyper-Mol: Molecular Representation Learning via Fingerprint-Based Hypergraph.

Computational intelligence and neuroscience
With the development of artificial intelligence (AI) in the field of drug design and discovery, learning informative representations of molecules is becoming crucial for those AI-driven tasks. In recent years, the graph neural networks (GNNs) have em...

Predicting Corrosion Damage in the Human Body Using Artificial Intelligence: In Vitro Progress and Future Applications.

The Orthopedic clinics of North America
Artificial intelligence (AI) is used in the clinic to improve patient care. While the successes illustrate AI's impact, few studies have led to improved clinical outcomes. In this review, we focus on how AI models implemented in nonorthopedic fields ...

Deep learning in sex estimation from knee radiographs - A proof-of-concept study utilizing the Terry Anatomical Collection.

Legal medicine (Tokyo, Japan)
Although knee measurements yield high classification rates in metric sex estimation, there is a paucity of studies exploring the knee in artificial intelligence-based sexing. This proof-of-concept study aimed to develop deep learning algorithms for s...

Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects.

Radiology
Filtered back projection (FBP) has been the standard CT image reconstruction method for 4 decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in several clinical applications. However, with faster and more advanced ...