AIMC Topic: Humans

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Tumor Segmentation in Intraoperative Fluorescence Images Based on Transfer Learning and Convolutional Neural Networks.

Surgical innovation
OBJECTIVE: To propose a transfer learning based method of tumor segmentation in intraoperative fluorescence images, which will assist surgeons to efficiently and accurately identify the boundary of tumors of interest.

A machine learning algorithm based on circulating metabolic biomarkers offers improved predictions of neurological diseases.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND AND AIMS: A machine learning algorithm based on circulating metabolic biomarkers for the predictions of neurological diseases (NLDs) is lacking. To develop a machine learning algorithm to compare the performance of a metabolic biomarker-ba...

The drug loading capacity prediction and cytotoxicity analysis of metal-organic frameworks using stacking algorithms of machine learning.

International journal of pharmaceutics
Metal-organic frameworks (MOFs) have shown excellent performance in the field of drug delivery. Despite the synthesis of a vast array of MOFs exceeding 100,000 varieties, certain formulations have exhibited suboptimal performance characteristics. The...

Comparing preferences for skin cancer screening: AI-enabled app vs dermatologist.

Social science & medicine (1982)
BACKGROUND AND AIM: Skin cancer is a major public health issue. While self-examinations and professional screenings are recommended, they are rarely performed. Mobile health (mHealth) apps utilising artificial intelligence (AI) for skin cancer screen...

Deep-learning-based real-time individualization for reduce-order haemodynamic model.

Computers in biology and medicine
The reduced-order lumped parameter model (LPM) has great computational efficiency in real-time numerical simulations of haemodynamics but is limited by the accuracy of patient-specific computation. This study proposed a method to achieve the individu...

PT-Finder: A multi-modal neural network approach to target identification.

Computers in biology and medicine
Efficient target identification for bioactive compounds, including novel synthetic analogs, is crucial for accelerating the drug discovery pipeline. However, the process of target identification presents significant challenges and is often expensive,...

Multicolor-Assay-on-a-Chip Processed by Robotic Operation (MACpro) with Improved Diagnostic Accuracy for Field-Deployable Detection.

Analytical chemistry
The ability to deploy decentralized laboratories with autonomous and reliable disease diagnosis holds the potential to deliver accessible healthcare services for public safety. While microfluidic technologies provide precise manipulation of small flu...

Editorial for the Special Issue "Sensing Brain Activity Using EEG and Machine Learning".

Sensors (Basel, Switzerland)
Sensing brain activity to reveal, analyze and recognize brain activity patterns has become a topic of great interest and ongoing research [...].

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data.

Sensors (Basel, Switzerland)
Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user's quality of life and safety, a...

Ballistocardial Signal-Based Personal Identification Using Deep Learning for the Non-Invasive and Non-Restrictive Monitoring of Vital Signs.

Sensors (Basel, Switzerland)
Owing to accelerated societal aging, the prevalence of elderly individuals experiencing solitary or sudden death at home has increased. Therefore, herein, we aimed to develop a monitoring system that utilizes piezoelectric sensors for the non-invasiv...