Browse Articles

This manuscript explores the performance of five different machine learning models in classifying brain tumors from a dataset of MRI scans. The authors find that several of the models showed >90% accuracy. Thus, the authors suggest that machine learning models demonstrate potential for effective implementation in clinical settings, including as a diagnostic tool that can be used to complement the expertise of neuroradiologists.

The authors looked at using computer vision to evaluate the degree of exotropia in individuals with strabismus.

The authors studied the impact of drying blood as a storage solution for space travel.

This paper looks at using spent coffee grounds as a partial substitute for titanium dioxide (TiO₂) as a catalyst for chemical reactions. Using UV-Vis spectrophotometry, they found that adding the coffee grounds to TiO₂ in a 3:1 ratio, there is still meaningful catalytic activity. This offers a cheaper solution than just using pure TiO₂.

The authors developed a quantum inspired model for stock market fluctuations.

The authors tested the impact of various additives on biopolymer degradation.

The study explored converting Gracilaria seaweed waste—known for releasing toxic hydrogen sulfide when decomposed—into biochar as a sustainable solution for waste management and soil improvement.

The authors looked at if there was any correlation between the phase of the moon and admissions for psychiatric concerns.

The authors looked at ways that seizures in patients with glioblastoma could be treated using C. elegans as a model system.

The author looked at how dance styles can vary by individuals, even between a student and their teacher.