Mid-Brain Connective for Human Information Processing: A New Strategy for the Science of Optimal Decision Making

Shetkar, Rashmi M.; Mohanty, Sachi Nandan

doi:10.1007/978-3-030-66869-3_4

Cited by 2 publications

(2 citation statements)

References 46 publications

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“…The authors introduce the concept of the mid-brain connective, proposing a model that focuses on optimizing the connections and integrations between the mind, brain, and body. This approach aims to empower individuals for more effective decision-making, ultimately contributing to their overall well-being [23].…”

Section: Machine Learning-based Modelsmentioning

confidence: 99%

Autism Spectrum Disorder Classification Using Machine Learning and Deep Learning- A Survey

S R,

Mounika

2023

EAI Endorsed Trans Perv Health Tech

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Modern, highly developed technology has impacted reputable procedures in the medical and healthcare industries. Smart healthcare prediction to the senior sick patient is not only for quick access to data but also to get dependable treatment in an accurate prediction by healthcare service provider. smart health prediction helps in the identification of numerous diseases. Based on patient experience, Deep learning technology provides a robust application space in the medical sector for health disease prediction problems by applying deep learning techniques to analyze various symptoms. In order to classify things and make precise predictions about diseases, deep learning techniques are utilized. people's health will be more secure, medical care will be of a higher caliber, and personal information will be kept more secret. As deep learning algorithms become more widely used to construct an interactive smart healthcare prediction and evaluation model on the basis of the deep learning model, CNN is upgraded. Advanced deep learning algorithms combined with multi-mode approaches and resting-state functional magnetic resonance represent an innovative approach that researchers have taken. A DL structure for the programmed ID ASD using highlights separated from the corpus callosum and cerebrum volume from the Stand dataset is proposed. Imaging is used to reveal hidden diseased brain connectome patterns to find diagnostic and prognostic indicators.

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Section: Machine Learning-based Modelsmentioning

confidence: 99%

Autism Spectrum Disorder Classification Using Machine Learning and Deep Learning- A Survey

S R,

Mounika

2023

EAI Endorsed Trans Perv Health Tech

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Section: Literature Reviewmentioning

confidence: 99%

Smart Fashion Recommendation System using FashionNet

Challa,

Sathwik,

Kiran

et al. 2023

ICST Transactions on Scalable Information Systems

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An intelligent system known as a fashion suggestion system gives consumers personalised fashion advice based on their tastes, style, body shape, and other variables. The system analyses a user's data and predicts the best fashion products for them using data analytics, machine learning, and artificial intelligence approaches. Intelligent fashion suggestion is currently desperately needed due to the explosive expansion of fashion-focused trends. We create algorithms that automatically recommend users' attire based on their own fashion tastes. We investigate the use of deep networks to this difficult problem. Our technology, called FashionNet, is made up of two parts: a matching network for determining compatibility and a feature network for feature extraction. We create a two-stage training method that transfers a broad compatibility model to a model that embeds personal choice in order to achieve personalised recommendation.

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Mid-Brain Connective for Human Information Processing: A New Strategy for the Science of Optimal Decision Making

Cited by 2 publications

References 46 publications

Autism Spectrum Disorder Classification Using Machine Learning and Deep Learning- A Survey

Autism Spectrum Disorder Classification Using Machine Learning and Deep Learning- A Survey

Smart Fashion Recommendation System using FashionNet

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