AIMC Journal:
npj biomedical innovations

Artificial intelligence-based cough analysis has emerged as a potential non-sputum approach for pulmonary tuberculosis triage and diagnostic support. This technical review synthesizes evidence from cough-based TB studies, highlighting current dataset...

Neurological disorders pose a growing global health burden, motivating advances in neural interfacing and artificial intelligence (AI). This review surveys state-of-the-art approaches for neural recording, stimulation and signal decoding and encoding...

sEMGCareHCI presents a low-cost, non-invasive surface electromyography (sEMG)-based system for recognizing finger positions and gestures from forearm muscle activity. The proposed "Spatio-Temporal Attention Model (STAM)" combines handcrafted time-dom...

A label-free high-frequency bioelectrical impedance spectroscopy method, coupled with supervised machine learning, was evaluated as an adjunct to histopathology by generating probability heat maps of excised dermal specimens to estimate the risk of b...

Pathological examination is the current gold standard in cancer diagnosis, yet artificial intelligence (AI) methods still struggle to capture the multi-scale heterogeneity of tumor morphology across patients, tissues, and magnifications. Here, we int...

The HeMonitor study evaluated the feasibility and accuracy of non-invasive hemoglobin (Hb) assessment using image-based techniques and machine learning in patients with hematologic malignancies. A total of 367 patients with hematologic malignancies a...