AIMC Topic: Humans

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c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer's disease.

BMC medical genomics
BACKGROUND: Alzheimer's disease (AD) is an incurable, debilitating neurodegenerative disorder. Current biomarkers for AD diagnosis require expensive neuroimaging or invasive cerebrospinal fluid sampling, thus precluding early detection. Blood-based b...

Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network.

BMC medical informatics and decision making
BACKGROUND: Important clinical information of patients is present in unstructured free-text fields of Electronic Health Records (EHRs). While this information can be extracted using clinical Natural Language Processing (cNLP), the recognition of nega...

A multimodal deep learning model for predicting severe hemorrhage in placenta previa.

Scientific reports
Placenta previa causes life-threatening bleeding and accurate prediction of severe hemorrhage leads to risk stratification and optimum allocation of interventions. We aimed to use a multimodal deep learning model to predict severe hemorrhage. Using M...

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.

Scientific reports
We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for patients with chronic kidney disease (CKD) using MRI Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images. The dataset comp...

Knowledge and Perception of the Use of AI and its Implementation in the Field of Radiology: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Artificial Intelligence (AI) has been developing for decades, but in recent years its use in the field of health care has experienced an exponential increase. Currently, there is little doubt that these tools have transformed clinical pra...

Development and validation of a CT-based deep learning algorithm to augment non-invasive diagnosis of idiopathic pulmonary fibrosis.

Respiratory medicine
RATIONALE: Non-invasive diagnosis of idiopathic pulmonary fibrosis (IPF) involves identification of usual interstitial pneumonia (UIP) pattern by computed tomography (CT) and exclusion of other known etiologies of interstitial lung disease (ILD). How...

Gastrointestinal tract disorders classification using ensemble of InceptionNet and proposed GITNet based deep feature with ant colony optimization.

PloS one
Computer-aided classification of diseases of the gastrointestinal tract (GIT) has become a crucial area of research. Medical science and artificial intelligence have helped medical experts find GIT diseases through endoscopic procedures. Wired endosc...

Differences Between Attending and Trainee Surgeon Performance Using Objective Performance Indicators During Robot-Assisted Lobectomy.

Innovations (Philadelphia, Pa.)
OBJECTIVE: Existing approaches for assessing surgical performance are subjective and prone to bias. In contrast, utilizing digital kinematic and system data from the surgical robot allows the calculation of objective performance indicators (OPIs) tha...

Beyond ChatGPT: What does GPT-4 add to healthcare? The dawn of a new era.

Cardiology journal
Over the past few years, artificial intelligence (AI) has significantly improved healthcare. Once the stuff of science fiction, AI is now widely used, even in our daily lives - often without us thinking about it. All healthcare professionals - especi...

Epigenetic target identification strategy based on multi-feature learning.

Journal of biomolecular structure & dynamics
The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics incr...