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AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

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Detecting physical abuse or neglect

Introduction

In the age of digital change, there is a wide application of ML, CV, and AI in different industries such as healthcare. These technologies have opened up new horizons in a number of areas, including the detection of physical abuse or neglect which has always been a problem for healthcare workers. ML, CV, and AI have brought new and innovative solutions for the identification, reporting, and prevention of such cases, which is a great help in this concerning aspect of healthcare.

Challenges

There are several barriers in the healthcare industry when it comes to identifying physical abuse or neglect. These are: Subjective interpretation of the signs and symptoms; low rates of reporting due to fear or doubt; absence of a uniform approach to screening for abuse; constraints in the resources that can be used for a detailed investigation; and the possibility of generating false positive results thus posing unjust consequences. Also, abuse or neglect can have signs that are quite vague and can be easily missed or mistaken for something else. Therefore, such challenges can lead to late intervention, insufficient assistance to the victims and more suffering.

AI Solutions

There are various challenges that affect the identification of abuse and neglect, and AI, ML, and CV provide valuable solutions to these problems. AI algorithms are capable of identifying the similarities and differences of medical images, patient information and other pertinent data which in turn improves the identification of abuse or neglect. For example, there is an on-going development of AI systems such as ‘DeepAIMed’ which are designed to pick up cues of child physical abuse from X-rays and other imaging modalities. Also, ML models are able to learn features that can help in distinguishing between usual and unusual patterns in electronic health records. CV, however, can be employed in surveillance to pick out symptoms of abuse or neglect in vivo. These systems are being deployed in institutions such as care homes to observe the patient-caregiver contact and any out of the ordinary behavior.

Benefits

There are many advantages of the use of AI, ML, and CV in healthcare. These technologies provide accurate and non-biased information thus minimizing on errors that may be caused by humans. They enable identification and treatment to be made early hence avoiding more severe conditions to occur to the victims. In addition, they enhance the delivery of health care services through simplifying some activities that would otherwise require the input of a health care professional. It also has the capacity of improving patient safety through tracking of the patient-caregiver contact and reporting any signs of harm to the patient.

Return on Investment

The ROI for AI, ML, and CV in identifying physical abuse or neglect is quite impressive. Although there is a significant investment required to purchase and develop these technologies, the return on investment in terms of reduced healthcare expenses, enhanced health status of patients, and avoidance of legal suits is quite high. In addition, these technologies can assist the healthcare givers in adhering to the set laws on patient safety thus averting charges and bad press.

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