AIMC Topic: Humans

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Beamforming-integrated neural networks for ultrasound imaging.

Ultrasonics
Sparse matrix beamforming (SMB) is a computationally efficient reformulation of delay-and-sum (DAS) beamforming as a single sparse matrix multiplication. This reformulation can potentially dovetail with machine learning platforms like TensorFlow and ...

ECG classification based on guided attention mechanism.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Integrating domain knowledge into deep learning models can improve their effectiveness and increase explainability. This study aims to enhance the classification performance of electrocardiograms (ECGs) by customizing specif...

Automated deep learning segmentation of cardiac inflammatory FDG PET.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Fluorodeoxyglucose positron emission tomography (FDG PET) with suppression of myocardial glucose utilization plays a pivotal role in diagnosing cardiac sarcoidosis. Reorientation of images to match perfusion datasets and myocardial segmen...

Prognostic insights after surgery for advances in understanding signet ring cell gastric cancer: a machine learning approach.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Signet ring cell (SRC) gastric carcinoma is traditionally associated with a poor prognosis. However, the literature has presented contradictory results. Linear models are the standard statistical tools typically used to study these condit...

Machine learning model to predict early recurrence in patients with perihilar cholangiocarcinoma planned treatment with curative resection: a multicenter study.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Early recurrence is the leading cause of death for patients with perihilar cholangiocarcinoma (pCCA) after surgery. Identifying high-risk patients preoperatively is important. This study aimed to construct a preoperative prediction model ...

Is artificial intelligence prepared for the 24-h shifts in the ICU?

Anaesthesia, critical care & pain medicine
Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient care and operational efficiency. ML algorithms can analyze vast amounts of data from electronic health records, physiological monitoring systems, and...

Stacking based ensemble learning framework for identification of nitrotyrosine sites.

Computers in biology and medicine
Protein nitrotyrosine is an essential post-translational modification that results from the nitration of tyrosine amino acid residues. This modification is known to be associated with the regulation and characterization of several biological function...

Two-stage deep learning framework for occlusal crown depth image generation.

Computers in biology and medicine
The generation of depth images of occlusal dental crowns is complicated by the need for customization in each case. To decrease the workload of skilled dental technicians, various computer vision models have been used to generate realistic occlusal c...

Designing nanotheranostics with machine learning.

Nature nanotechnology
The inherent limits of traditional diagnoses and therapies have driven the development and application of emerging nanotechnologies for more effective and safer management of diseases, herein referred to as 'nanotheranostics'. Although many important...

Deep learning predicted perceived age is a reliable approach for analysis of facial ageing: A proof of principle study.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Perceived age (PA) has been associated with mortality, genetic variants linked to ageing and several age-related morbidities. However, estimating PA in large datasets is laborious and costly to generate, limiting its practical applicabili...