A New Mindset: Artificial Intelligence in Digital Hearing Aids

Neha Taneja*

A New Mindset: Artificial Intelligence in Digital Hearing Aids.

Artificial intelligence has a wider scope of its applications in every domain nowadays. Artificial intelligence in general, refers to the field of computer science which generates, uses computer programs to solve complex problems and provides intelligent solutions. For this procedure, several different rules, algorithms, and software can be used.

When the healthcare industry is considered, AI has been used extensively. Techniques of AI assists physicians in clinical decision making i.e., radiology and tackling various diseases2 such as cancer neurology and cardiology. Analysis of big data can be easily obtained by the clinician into a required clinical chunk of data by techniques used in AI.

Additionally, the big success of AI in medical literature has been in segregating larger chunks of
relevant clinical data from large medical records of patients via the
use of sophisticated algorithms which may help in achieving efficient clinical decision-making.

AI helps further to physicians to render quality patient care by chunking larger updated information
from various sources such as textbooks, clinical practices, and journals. In addition, AI technology helps in better medical results with fewer errors in — diagnostic and therapeutic as evidenced
more with humans clinical practice.

In a similar trend in the hearing healthcare industry, artificial intelligence has been found to be widely in use. Artificial intelligence with reference to amplification devices — digital hearing aids can be understood as a vehicle or platform which facilitates audibility and assists in communication via the use of advanced algorithm and software.

With the advancement in technology from analog to digital, listening performance has been enhanced for hearing impaired users. But the standard term “digital” doesn’t imply all digital hearing aids are the same.

Otolaryngol Open J. 2020; 6(1): e1-e3. doi: 10.17140/OTLOJ-6-e007

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