AIMC Topic: Machine Learning

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Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

Biosensors & bioelectronics
Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate eryt...

ApoplastP: prediction of effectors and plant proteins in the apoplast using machine learning.

The New phytologist
The plant apoplast is integral to intercellular signalling, transport and plant-pathogen interactions. Plant pathogens deliver effectors both into the apoplast and inside host cells, but no computational method currently exists to discriminate betwee...

Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.

EBioMedicine
BACKGROUND: Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability.

Automated computer-based detection of encounter behaviours in groups of honeybees.

Scientific reports
Honeybees form societies in which thousands of members integrate their behaviours to act as a single functional unit. We have little knowledge on how the collaborative features are regulated by workers' activities because we lack methods that enable ...

Forecasting influenza-like illness dynamics for military populations using neural networks and social media.

PloS one
This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of histo...

A 29-gene and cytogenetic score for the prediction of resistance to induction treatment in acute myeloid leukemia.

Haematologica
Primary therapy resistance is a major problem in acute myeloid leukemia treatment. We set out to develop a powerful and robust predictor for therapy resistance for intensively treated adult patients. We used two large gene expression data sets (n=856...

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.

Computational and mathematical methods in medicine
High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional me...

Tracking Gaze and Visual Focus of Attention of People Involved in Social Interaction.

IEEE transactions on pattern analysis and machine intelligence
The visual focus of attention (VFOA) has been recognized as a prominent conversational cue. We are interested in estimating and tracking the VFOAs associated with multi-party social interactions. We note that in this type of situations the participan...