AIMC Topic: Humans

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Deep Learning Detection of Active Pulmonary Tuberculosis at Chest Radiography Matched the Clinical Performance of Radiologists.

Radiology
Background The World Health Organization (WHO) recommends chest radiography to facilitate tuberculosis (TB) screening. However, chest radiograph interpretation expertise remains limited in many regions. Purpose To develop a deep learning system (DLS)...

Photon-counting Detector CT with Deep Learning Noise Reduction to Detect Multiple Myeloma.

Radiology
Background Photon-counting detector (PCD) CT and deep learning noise reduction may improve spatial resolution at lower radiation doses compared with energy-integrating detector (EID) CT. Purpose To demonstrate the diagnostic impact of improved spatia...

IDT: An incremental deep tree framework for biological image classification.

Artificial intelligence in medicine
Nowadays, breast and cervical cancers are respectively the first and fourth most common causes of cancer death in females. It is believed that, automated systems based on artificial intelligence would allow the early diagnostic which increases signif...

Do people with multiple sclerosis perceive upper limb improvements from robotic-mediated therapy? A mixed methods study.

Multiple sclerosis and related disorders
BACKGROUND: Robot-mediated training is increasingly considered as a rehabilitation intervention targeting upper limb disability. However, experiences of such an intervention have been rarely explored in the multiple sclerosis population. This mixed m...

Machine learning and deep learning modeling and simulation for predicting PM2.5 concentrations.

Chemosphere
Particulate matter (PM) pollution greatly endanger human physical and mental health, and it is of great practical significance to predict PM concentrations accurately. This study measured one-year monitoring data of six main meteorological parameters...

A multi-scale evolutionary deep learning model based on CEEMDAN, improved whale optimization algorithm, regularized extreme learning machine and LSTM for AQI prediction.

Environmental research
With the rapid development of economy, air pollution occurs frequently, which has a huge negative impact on human health and urban ecosystem. Air quality index (AQI) can directly reflect the degree of air pollution. Accurate AQI trend prediction can ...

Robot-assisted transthoracic hybrid esophagectomy versus open and laparoscopic hybrid esophagectomy: propensity score matched analysis of short-term outcome.

Langenbeck's archives of surgery
PURPOSE: Minimally invasive en-bloc esophagectomy is associated with a reduction of postoperative morbidity. This was demonstrated for both total minimally invasive and hybrid esophagectomy. However, little is known about any benefits of robotic assi...

Artificial intelligence system for training diagnosis and differentiation with molar incisor hypomineralization (MIH) and similar pathologies.

Clinical oral investigations
OBJECTIVES: Molar incisor hypomineralization (MIH) is a difficult-to-diagnose developmental disorder of the teeth, mainly in children and adolescents. Due to the young age of the patients, problems typically occur with the diagnosis of MIH. The aim o...

Beyond fine-tuning: Classifying high resolution mammograms using function-preserving transformations.

Medical image analysis
The task of classifying mammograms is very challenging because the lesion is usually small in the high resolution image. The current state-of-the-art approaches for medical image classification rely on using the de-facto method for convolutional neur...