AIMC Topic: Humans

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Artificial intelligence-driven pharmaceutical industry: A paradigm shift in drug discovery, formulation development, manufacturing, quality control, and post-market surveillance.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
The advent of artificial intelligence (AI) has catalyzed a profound transformation in the pharmaceutical industry, ushering in a paradigm shift across various domains, including drug discovery, formulation development, manufacturing, quality control,...

Real-time sub-milliwatt epilepsy detection implemented on a spiking neural network edge inference processor.

Computers in biology and medicine
Analyzing electroencephalogram (EEG) signals to detect the epileptic seizure status of a subject presents a challenge to existing technologies aimed at providing timely and efficient diagnosis. In this study, we aimed to detect interictal and ictal p...

Artificial intelligence-assisted oculo-gait measurements for cognitive impairment in cerebral small vessel disease.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Oculomotor and gait dysfunctions are closely associated with cognition. However, oculo-gait patterns and their correlation with cognition in cerebral small vessel disease (CSVD) remain unclear.

An evaluation of the performance of stopping rules in AI-aided screening for psychological meta-analytical research.

Research synthesis methods
Several AI-aided screening tools have emerged to tackle the ever-expanding body of literature. These tools employ active learning, where algorithms sort abstracts based on human feedback. However, researchers using these tools face a crucial dilemma:...

Enhancing bridge damage detection with Mamba-Enhanced HRNet for semantic segmentation.

PloS one
With the acceleration of urbanization, bridges, as crucial infrastructure, their structural health and stability are paramount to public safety. This paper proposes Mamba-Enhanced HRNet for bridge damage detection. Mamba-Enhanced HRNet integrates the...

Fixing imbalanced binary classification: An asymmetric Bayesian learning approach.

PloS one
Most statistical and machine learning models used for binary data modeling and classification assume that the data are balanced. However, this assumption can lead to poor predictive performance and bias in parameter estimation when there is an imbala...

Machine learning algorithms to predict treatment success for patients with pulmonary tuberculosis.

PloS one
Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by the Mycobacterium TB bacteria, continues to pose a serious threat to world health. The TB diagnosis phase includes a patient's medical history, physic...

USCT-UNet: Rethinking the Semantic Gap in U-Net Network From U-Shaped Skip Connections With Multichannel Fusion Transformer.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Medical image segmentation is a crucial component of computer-aided clinical diagnosis, with state-of-the-art models often being variants of U-Net. Despite their success, these models' skip connections introduce an unnecessary semantic gap between th...

Novel multimodal sensing and machine learning strategies to classify cognitive workload in laparoscopic surgery.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Surgeons can experience elevated cognitive workload (CWL) during surgery due to various factors including operative technicalities and the environmental demands of the operating theatre. This can result in poorer outcomes and have a detri...