AIMC Topic: Artificial Intelligence

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Multimodality Imaging and Artificial Intelligence for Tumor Characterization: Current Status and Future Perspective.

Seminars in nuclear medicine
Research in medical imaging has yet to do to achieve precision oncology. Over the past 30 years, only the simplest imaging biomarkers (RECIST, SUV,…) have become widespread clinical tools. This may be due to our inability to accurately characterize t...

Agent-oriented Decision Support System for Business Processes Management with Genetic Algorithm Optimization: an Application in Healthcare.

Journal of medical systems
Agent-based approaches have been known to be appropriate as systems and methods in medical administration in recent years. The increased attention to processes led to the recent growth of Business Process Management discipline, which quite exclusivel...

Artificial Intelligence and Mechanistic Modeling for Clinical Decision Making in Oncology.

Clinical pharmacology and therapeutics
The amount of "big" data generated in clinical oncology, whether from molecular, imaging, pharmacological, or biological origin, brings novel challenges. To mine efficiently this source of information, mathematical models able to produce predictive a...

Effectiveness of Artificial Intelligence Applications Designed for Endodontic Diagnosis, Decision-making, and Prediction of Prognosis: A Systematic Review.

The journal of contemporary dental practice
AIM: With advancements in science and technology, there has been phenomenal developments in the application of neural networks in dentistry. This systematic review aimed to report on the effectiveness of artificial intelligence (AI) applications desi...

Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review.

Journal of medical systems
The term machine learning refers to a collection of tools used for identifying patterns in data. As opposed to traditional methods of pattern identification, machine learning tools relies on artificial intelligence to map out patters from large amoun...

A Comparative Analysis of Visual Encoding Models Based on Classification and Segmentation Task-Driven CNNs.

Computational and mathematical methods in medicine
Nowadays, visual encoding models use convolution neural networks (CNNs) with outstanding performance in computer vision to simulate the process of human information processing. However, the prediction performances of encoding models will have differe...

A Simple Method to Train the AI Diagnosis Model of Pulmonary Nodules.

Computational and mathematical methods in medicine
BACKGROUND: The differential diagnosis of subcentimetre lung nodules with a diameter of less than 1 cm has always been one of the problems of imaging doctors and thoracic surgeons. We plan to create a deep learning model for the diagnosis of pulmonar...

Artificial Intelligence in Lung Cancer: Bridging the Gap Between Computational Power and Clinical Decision-Making.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Lung cancer remains the most common cause of cancer death worldwide. Recent advances in lung cancer screening, radiotherapy, surgical techniques, and systemic therapy have led to increasing complexity in diagnosis, treatment decision-making, and asse...

Utilizing Artificial Intelligence for Head and Neck Cancer Outcomes Prediction From Imaging.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Artificial intelligence (AI)-based models have become a growing area of interest in predictive medicine and have the potential to aid physician decision-making to improve patient outcomes. Imaging and radiomics play an increasingly important role in ...