AIMC Topic: Algorithms

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Success History Adaptive Competitive Swarm Optimizer with Linear Population Reduction: Performance benchmarking and application in eye disease detection.

Computers in biology and medicine
Eye disease detection has achieved significant advancements thanks to artificial intelligence (AI) techniques. However, the construction of high-accuracy predictive models still faces challenges, and one reason is the deficiency of the optimizer. Thi...

Characterizing Chinese saffron Origin, Age and grade using VNlR hyperspectral imaging and Machine learning.

Food research international (Ottawa, Ont.)
Saffron (Crocus sativus L.), the dried stigma, is an extremely valuable spice and medicinal herb, whose economic value is affected by geographical origin, age and grade. In this study, we proposed a method to identify saffron from different Chinese o...

Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants.

ACS applied materials & interfaces
Current limitations in implant design often lead to trade-offs between minimally invasive surgery and achieving the desired post-implantation functionality. Here, we present an artificial intelligence inverse design paradigm for creating deployable i...

Machine Learning for Reaction Performance Prediction in Allylic Substitution Enhanced by Automatic Extraction of a Substrate-Aware Descriptor.

Journal of chemical information and modeling
Despite remarkable advancements in the organic synthesis field facilitated by the use of machine learning (ML) techniques, the prediction of reaction outcomes, including yield estimation, catalyst optimization, and mechanism identification, continues...

Effective Dose Estimation in Computed Tomography by Machine Learning.

Tomography (Ann Arbor, Mich.)
BACKGROUND: Computed tomography scans are widely used in everyday medical practice due to speed, image reliability, and detectability of a wide range of pathologies. Each scan exposes the patient to a radiation dose, and performing a fast estimation ...

Estimating Visual Acuity With Spectacle Correction From Fundus Photos Using Artificial Intelligence.

JAMA network open
IMPORTANCE: Determining spectacle-corrected visual acuity (VA) is essential when managing many ophthalmic diseases. If artificial intelligence (AI) evaluations of macular images estimated this VA from a fundus image, AI might provide spectacle-correc...

Predicting autoimmune thyroiditis in primary Sjogren's syndrome patients using a random forest classifier: a retrospective study.

Arthritis research & therapy
BACKGROUND: Primary Sjogren's syndrome (pSS) and autoimmune thyroiditis (AIT) share overlapping genetic and immunological profiles. This retrospective study evaluates the efficacy of machine learning algorithms, with a focus on the Random Forest Clas...

Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network.

Scientific reports
Steady-State Visually Evoked Potential (SSVEP) signals can be decoded by either a traditional machine learning algorithm or a deep learning network. Combining the two methods is expected to enhance the performance of an SSVEP-based brain-computer int...

pACP-HybDeep: predicting anticancer peptides using binary tree growth based transformer and structural feature encoding with deep-hybrid learning.

Scientific reports
Worldwide, Cancer remains a significant health concern due to its high mortality rates. Despite numerous traditional therapies and wet-laboratory methods for treating cancer-affected cells, these approaches often face limitations, including high cost...

Tumor detection on bronchoscopic images by unsupervised learning.

Scientific reports
The diagnosis and early identification of intratracheal tumors relies on the experience of the operators and the specialists. Operations by physicians with insufficient experience may lead to misdiagnosis or misjudgment of tumors. To address this iss...