AIMC Topic: Deep Learning

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Identification of a clonal population of Aspergillus flavus by MALDI-TOF mass spectrometry using deep learning.

Scientific reports
The spread of fungal clones is hard to detect in the daily routines in clinical laboratories, and there is a need for new tools that can facilitate clone detection within a set of strains. Currently, Matrix Assisted Laser Desorption-Ionization Time-o...

Using deep learning models to analyze the cerebral edema complication caused by radiotherapy in patients with intracranial tumor.

Scientific reports
Using deep learning models to analyze patients with intracranial tumors, to study the image segmentation and standard results by clinical depiction complications of cerebral edema after receiving radiotherapy. In this study, patients with intracrania...

Deep-learning online EEG decoding brain-computer interface using error-related potentials recorded with a consumer-grade headset.

Biomedical physics & engineering express
Brain-computer interfaces (BCIs) allow subjects with sensorimotor disability to interact with the environment. Non-invasive BCIs relying on EEG signals such as event-related potentials (ERPs) have been established as a reliable compromise between spa...

A Novel Molecular Representation Learning for Molecular Property Prediction with a Multiple SMILES-Based Augmentation.

Computational intelligence and neuroscience
Deep learning has brought a rapid development in the aspect of molecular representation for various tasks, such as molecular property prediction. The prediction of molecular properties is a crucial task in the field of drug discovery for finding spec...

Application of Deep Learning in Civil Engineering Management.

Computational intelligence and neuroscience
Construction safety issues are of great significance in civil engineering management. In this paper, the entry point is the recognition of workers wearing helmets during the construction process, and the recognition performance is improved by combini...

Construction of a Hybrid Teaching Model System Based on Promoting Deep Learning.

Computational intelligence and neuroscience
The rapid development of computer network technology in today's society has also brought new opportunities for the transformation of the teaching management mode of colleges and universities. Nowadays, most colleges and universities are gradually imp...

: An Automated Diagnosis of Pulmonary Fibrosis Progression Prediction Using Honeycombing and Deep Learning.

Computational intelligence and neuroscience
Pulmonary fibrosis is a severe chronic lung disease that causes irreversible scarring in the tissues of the lungs, which results in the loss of lung capacity. The Forced Vital Capacity () of the patient is an interesting measure to investigate this d...

Validation of a deep learning-based image analysis system to diagnose subclinical endometritis in dairy cows.

PloS one
The assessment of polymorphonuclear leukocyte (PMN) proportions (%) of endometrial samples is the hallmark for subclinical endometritis (SCE) diagnosis. Yet, a non-biased, automated diagnostic method for assessing PMN% in endometrial cytology slides ...

Deep learning via LSTM models for COVID-19 infection forecasting in India.

PloS one
The COVID-19 pandemic continues to have major impact to health and medical infrastructure, economy, and agriculture. Prominent computational and mathematical models have been unreliable due to the complexity of the spread of infections. Moreover, lac...

Positional SHAP (PoSHAP) for Interpretation of machine learning models trained from biological sequences.

PLoS computational biology
Machine learning with multi-layered artificial neural networks, also known as "deep learning," is effective for making biological predictions. However, model interpretation is challenging, especially for sequential input data used with recurrent neur...