Just look at some EM articles, see screen shot the bottom two...

Just look at some EM articles, see screen shot the bottom two reference staff that are on EMV payroll




Also they are very technical
The bottom abstract is thus:

Based on the hypothesis that healthy human brains are highly symmetric along the sagittal plane, a method to detect and localize brain injuries using the intersection of pairs of signals captured by symmetrical antennas surrounding the head is presented. The method localizes the target using information at the low-frequency band, whereas the shape of the target is estimated using information from the high-frequency band. Then, an intersection of two pairs of antennas enables identifying the position of the target. Finally, a heat map is used to visualize the injury. The results indicate that crossing pairs of signals from the hemisphere with injury exhibit significantly different amplitudes in the graph features compared to those not crossing the target ( p < 0.003). The experiments show that the proposed localization algorithm can achieve an accuracy of 0.85 ± 0.08 Dice similarity coefficient based on 150 experimental measurements on head phantoms.

So I have given Chat GPT 12 yo level summaries

Scientists have come up with a way to find and locate brain injuries by using special antennas placed around the head. They noticed that healthy brains are very similar on each side, so they used this idea to create a method. They capture signals from these antennas and use them to figure out where the injury is in the brain. They use different frequencies of signals to find the position and shape of the injury. By comparing the signals, they can make a map that shows where the injury is. When they tested this method, it was accurate about 85% of the time based on experiments they did with models of heads.



2nd article

This article talks about using a special kind of computer program called deep learning to help find things using microwaves. Deep learning is really good at recognizing patterns, but sometimes it's hard to understand why it makes the decisions it does. This makes it tricky to use in important things like finding strokes in the brain. The article suggests a way to make deep learning more understandable by using a technique called Grad-CAM. This technique helps to show why the program thinks something is there by highlighting important parts of the picture it's looking at. By doing this, it helps people trust the program more because they can see why it thinks what it does. The article says that this method helps the computer learn better and gives results that make sense.


1st Article
the abstract and then ChatGPT - I LIKE how the AI says "CLEVER TECHNIQUES" to make it easier for me to understand.

A tapered graded index (GRIN) lens antenna that aims at enhancing electromagnetic penetration into human torso by generating focused planar near-field radiation is presented. The antenna is composed of a four-layer lens excited by a modified slot antenna. Each layer of the lens case is filled with fabricated mixtures of engineered materials that have specific relative permittivity values. The exciting antenna is made compact by utilizing meandered feed lines and substrate folded technique. The number of layers of the lens and the specification of each layer are determined by minimizing the generalized reflection coefficient of the antenna. A focused plan- wave radiation is achieved by tapering the lens based on the theory of total internal reflection. The study of E-field quality inside the torso demonstrates that the proposed lens successfully converts spherical wave radiation into a local plane-wave radia- tion, resulting in 11 dB improvement in wave penetration inside the torso compared to the body-matched antenna (without lens). The measured results show that the antenna operates over a wide band from 0.43 to 1.85 GHz (125% fractional bandwidth), which is a merit for the torso imaging application. Furthermore, the antenna has the physical size of 110 × 110 × 48 mm3, corresponding to 0.15 × 0.15 × 0.06λ30 , where λ0 is the wavelength at the lowest working frequency. The results indicate that the antenna accomplishes 4.9 dB (209% improvement) stronger wave penetration inside the torso compared to other existing GRIN lens antennas.


ChatGPT
This article talks about a special kind of antenna that helps electromagnetic waves go deeper into the human body. They made this antenna by using layers of different materials that help focus the waves. They also made the antenna small by using clever techniques. The antenna sends out waves in a way that they go straight into the body, which is better than other antennas. The tests showed that this antenna works well over a wide range of frequencies and is smaller than others while being more effective at sending waves into the body.