The authors studied the accuracy of two commonly used explainable AI techniques for detecting pneumonia in chest x-rays.
Read More...Lung region complexity affects Grad-CAM and Deep Taylor outcomes in pneumonia predictions
The authors studied the accuracy of two commonly used explainable AI techniques for detecting pneumonia in chest x-rays.
Read More...Alpha-amylase inhibitors: Cinnamomum cassia and Camellia sinensis extracts against type II diabetes
α-amylase breaks down starch into glucose, which can cause blood sugar spikes and increase the risk of type II diabetes. This study tested natural extracts from cassia cinnamon and green tea as alternatives to synthetic inhibitors like acarbose, which can be costly and cause side effects.
Read More...Reinforcement learning in 2-D space with varying gravitational fields
In this study the authors looked at the ability to navigate planes in space between randomly placed planets. They used machine and reinforcement learning to run simulations and found that they were able to identify optimal paths for travel. In the future these techniques may allow for safer travel in unknown spaces.
Read More...Designing gRNAs to reduce the expression of the DMPK gene in patients with classic myotonic dystrophy
The authors describe the design and testing of new guide RNAs targeting the DMPK gene, which is responsible for myotonic dystrophy.
Read More...Changing the surface properties of the backside of a silicon wafer to repel oil and prevent particle binding
Wafers, essential in microchip production, can develop issues like leveling problems and wafer slip due to the formation of silanol bonds on their backside, which attract silica particles and oil. Authors tested addressing this issue with a coating of [acetoxy(polyethyleneoxy)propyl]triethoxysilane (APTS) applied to the wafer’s backside, preventing particle binding and oil adherence.
Read More...Unveiling bias in ChatGPT-3.5: Analyzing constitutional AI principles for politically biased responses
Various methods exist to mitigate bias in AI models, including "Constitutional AI," a technique which guides the AI to behave according to a list of rules and principles. Lo, Poosarla, Singhal, Li, Fu, and Mui investigate whether constitutional AI can reduce bias in AI outputs on political topics.
Read More...Examining the prevalence of depression in coronary artery disease patients: a cross-sectional analysis
The authors surveyed individuals diagnosed with coronary artery disease about their mental health to study a potential connection between coronary artery disease and depression.
Read More...Effects of material advantage and space advantage on the Komodo and Stockfish chess engines
Chess engines, or computer programs built to play chess, outperform even the best human players. Kaushikan and Park investigate the inner workings of these chess engines by studying popular chess engines' evaluations of which side of a chess match is most likely to win, and how this is affected by the number of pieces and controlled squares on each side.
Read More...Evaluating TensorFlow image classification in classifying proton collision images for particle colliders
In this study the authors looked at developing a more efficient particle collision classification method with the goal of being able to more efficiently analyze particle trajectories from large-scale particle collisions without loss of accuracy.
Read More...Structure-activity relationship of berberine and G4 DNA reveals aromaticity’s effect on binding affinity
Berberine is a natural quaternary alkaloid that has anti-microbial and anti-cancer effects. This compound can bind to Guanine Quadruplex (G4) DNA secondary complexes to help inhibit cancer cell proliferation. In this study, the authors investigate whether incorporating large aromatic rings helps to stabilize berberine-G4 interactions.
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