AIMC Topic: Artificial Intelligence

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Digging deeper on "deep" learning: A computational ecology approach.

The Behavioral and brain sciences
We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of ...

Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human-like learning.

The Behavioral and brain sciences
Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous lear...

What can the brain teach us about building artificial intelligence?

The Behavioral and brain sciences
Lake et al. offer a timely critique on the recent accomplishments in artificial intelligence from the vantage point of human intelligence and provide insightful suggestions about research directions for building more human-like intelligence. Because ...

The architecture challenge: Future artificial-intelligence systems will require sophisticated architectures, and knowledge of the brain might guide their construction.

The Behavioral and brain sciences
In this commentary, we highlight a crucial challenge posed by the proposal of Lake et al. to introduce key elements of human cognition into deep neural networks and future artificial-intelligence systems: the need to design effective sophisticated ar...

Using Semantic Technologies to Extract Highlights from Care Notes.

Studies in health technology and informatics
We propose a cognitive system for patient-centric care that leverages and combines natural language processing, semantics, and learning from users over time to support care professionals working with large volumes of patient notes. The proposed metho...

Identifying Chemical-Disease Relationship in Biomedical Text Using a Multiple Kernel Learning-Boosting Method.

Studies in health technology and informatics
Chemical-induced disease relations (CID) are crucial in various biomedical tasks. In the CID task of Biocreative V, no classifiers with multiple kernels have been developed. In this study, a multiple kernel learning-boosting (MKLB) method is proposed...

Prediction and Factor Extraction of Drug Function by Analyzing Medical Records in Developing Countries.

Studies in health technology and informatics
The World Health Organization has declared Bangladesh one of 58 countries facing acute Human Resources for Health (HRH) crisis. Artificial intelligence in healthcare has been shown to be successful for diagnostics. Using machine learning to predict p...

An Infrared Thermal Images Database and a New Technique for Thyroid Nodules Analysis.

Studies in health technology and informatics
Thyroid nodules diseases are a common health problem and thyroidal cancer is becoming increasingly prevalent. They appear in the neck and bottom neck region, superficially over the trachea. Cancer tissues are characterized by higher temperatures than...