AIMC Topic: Algorithms

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Using AI/ML to predict blending performance and process sensitivity for Continuous Direct Compression (CDC).

International journal of pharmaceutics
Utilising three artificial intelligence (AI)/machine learning (ML) tools, this study explores the prediction of fill level in inclined linear blenders at steady state by mapping a wide range of bulk powder characteristics to processing parameters. Pr...

psoResNet: An improved PSO-based residual network search algorithm.

Neural networks : the official journal of the International Neural Network Society
Neural Architecture Search (NAS) methods are widely employed to address the time-consuming and costly challenges associated with manual operation and design of deep convolutional neural networks (DCNNs). Nonetheless, prevailing methods still encounte...

An artificial intelligence approach to predict infants' health status at birth.

International journal of medical informatics
BACKGROUND: Machine learning could be used for prognosis/diagnosis of maternal and neonates' diseases by analyzing the data sets and profiles obtained from a pregnant mother.

PatentNetML: A Novel Framework for Predicting Key Compounds in Patents Using Network Science and Machine Learning.

Journal of medicinal chemistry
Patents play a crucial role in drug research and development, providing early access to unpublished data and offering unique insights. Identifying key compounds in patents is essential to finding novel lead compounds. This study collected a comprehen...

The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas.

International journal of molecular sciences
Even if malaria is rare in Europe, it is a medical emergency and programs for its control should ensure both an early diagnosis and a prompt treatment within 24-48 h from the onset of the symptoms. The increasing number of imported malaria cases as w...

Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinoma.

Scientific reports
To examine the comparative robustness of computed tomography (CT)-based conventional radiomics and deep-learning convolutional neural networks (CNN) to predict overall survival (OS) in HCC patients. Retrospectively, 114 HCC patients with pretherapeut...

Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study.

Frontiers in public health
OBJECTIVE: The study aimed to use supervised machine learning models to predict the length and risk of prolonged hospitalization in PLWHs to help physicians timely clinical intervention and avoid waste of health resources.

Revolutionizing Breast Cancer Care: AI-Enhanced Diagnosis and Patient History.

Computer methods in biomechanics and biomedical engineering
Breast cancer poses a significant global health challenge, demanding enhanced diagnostic accuracy and streamlined medical history documentation. This study presents a holistic approach that harnesses the power of artificial intelligence (AI) and mach...

Evaluation of accuracy of deep learning and conventional neural network algorithms in detection of dental implant type using intraoral radiographic images: A systematic review and meta-analysis.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: With the growing importance of implant brand detection in clinical practice, the accuracy of machine learning algorithms in implant brand detection has become a subject of research interest. Recent studies have shown promising r...