AIMC Topic: Humans

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Landet: an efficient physics-informed deep learning approach for automatic detection of anatomical landmarks and measurement of spinopelvic alignment.

Journal of orthopaedic surgery and research
PURPOSE: An efficient physics-informed deep learning approach for extracting spinopelvic measures from X-ray images is introduced and its performance is evaluated against manual annotations.

Application of machine learning methods for predicting under-five mortality: analysis of Nigerian demographic health survey 2018 dataset.

BMC medical informatics and decision making
BACKGROUND: Under-five mortality remains a significant public health issue in developing countries. This study aimed to assess the effectiveness of various machine learning algorithms in predicting under-five mortality in Nigeria and identify the mos...

A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm.

Scientific reports
We constructed an early prediction model for postoperative pulmonary complications after thoracoscopic surgery using machine learning and deep learning algorithms. The artificial intelligence prediction models were built in Python, primarily using ar...

Research on helmet wearing detection method based on deep learning.

Scientific reports
The vigorous development of the construction industry has also brought unprecedented safety risks. The wearing of safety helmets at the construction site can effectively reduce casualties. As a result, this paper suggests employing a deep learning-ba...

Integrated image and location analysis for wound classification: a deep learning approach.

Scientific reports
The global burden of acute and chronic wounds presents a compelling case for enhancing wound classification methods, a vital step in diagnosing and determining optimal treatments. Recognizing this need, we introduce an innovative multi-modal network ...

Clinical efficiency of three-port inflatable robot-assisted thoracoscopic surgery in mediastinal tumor resection.

World journal of surgical oncology
BACKGROUND: Aimed to assess clinical effect of three-port inflatable robot-assisted thoracoscopic surgery in mediastinal tumor resection by comparing results of the robot group with the video group.

Theranostics and artificial intelligence: new frontiers in personalized medicine.

Theranostics
The field of theranostics is rapidly advancing, driven by the goals of enhancing patient care. Recent breakthroughs in artificial intelligence (AI) and its innovative theranostic applications have marked a critical step forward in nuclear medicine, l...

Advancements in technology for characterizing the tumor immune microenvironment.

International journal of biological sciences
Immunotherapy plays a key role in cancer treatment, however, responses are limited to a small number of patients. The biological basis for the success of immunotherapy is the complex interaction between tumor cells and tumor immune microenvironment (...

Non-invasive prediction for pathologic complete response to neoadjuvant chemoimmunotherapy in lung cancer using CT-based deep learning: a multicenter study.

Frontiers in immunology
Neoadjuvant chemoimmunotherapy has revolutionized the therapeutic strategy for non-small cell lung cancer (NSCLC), and identifying candidates likely responding to this advanced treatment is of important clinical significance. The current multi-instit...

Using artificial intelligence to predict choledocholithiasis: can machine learning models abate the use of MRCP in patients with biliary dysfunction?

ANZ journal of surgery
BACKGROUND: Prompt diagnosis of choledocholithiasis is crucial for reducing disease severity, preventing complications and minimizing length of stay. Magnetic resonance cholangiopancreatography (MRCP) is commonly used to evaluate patients with suspec...